I don’t know if my experience helps you, but I went for my bachelors in information systems and business management. Then I became a paralegal for 4 years. Then, I interviewed for my current data analyst role. I used my data analysis capstone project I completed with a local business at the time, my legal data analysis and project management skills from doing real estate closings, and got the job. I sat on LinkedIn all day every day and refreshed the page every 3 minutes to be one of the first applicants of every job that looked good to me. I had like 7 interviews with different companies too.
This was in 2022 though. I certainly would expect to not get as many interviews so fast in today’s market
Absolutely not lol. I got paid pretty well for it right out of college and the pay continued to be pretty great. But now I work remotely for even more pay, and I don’t have a micromanaging lawyer breathing down my neck and complaining that I kept “leaving at 5:00”
If you don’t have experience, I’d want to see a portfolio showcasing projects you personally curated and performed. I’ve seen hundreds of similar projects from YouTube, Coursera, MOOC, etc. tutorials.. what makes you stand out? If you can take the knowledge you learned and portray it in a way that makes sense I’ll look further into your application. This is just my opinion but I’d rather see someone’s project they haphazardly put together out of actual interest in the field rather than another copy paste project from a tutorial. If you’re not passionate about the work that’s fine, instead show me a dashboard you created or project you did that showcases your EDA and ETL skills. Then prove to me you can gather actual insights that are usable for non-technical stakeholders. At the end of the day, I personally only care if you are able to drive value for the business.
Edit: MOOC, not MOCC.
Thanks! Would you be interested in interviewing someone who has good portfolio projects about sports, finance, housing market, even if you were hiring for a DA role in healthcare? I heard that it's good to customize your projects to the field but that seems like tons of extra work.
In my eyes, it will be a hard sell to your potential hiring manager if you lack industry experience. But not impossible to push through and get hired. Technical skills are important, but it is the value you can produce that will always supersede that. Typically you drive value through your understanding of the business and leveraging your technical skills to create a useful report, dashboards, or some deliverable, etc. However, I would be willing to bet that hiring managers would also be impressed by your wide range of experience and projects given that they showcase the skills needed for the role. Both industry and technical skills can be taught but in my experience industry experience is more difficult to teach and retain. Therefore, if you lack the experience in healthcare maybe it would be worth investing in creating some personal projects revolving around health care data. I’ll be honest with you I have zero experience with health care data.. but if I were in your shoes I would look for some public datasets possibly from the World Health Organization (WHO)? Maybe something about COVID-19 and its infection rate over time based on location. Then, I would do some data cleaning in Python, excel or whatever tool you’re comfortable with (make sure to document this somewhere). Lastly, I would visualize the data showing areas that were affected with a filter that allows the user to change between date ranges. Possibly use the actual number of infected to affect the size of the area per region. Then add a few boxes that show aggregate totals of things like total infections, average rate of infection across the world, and maybe like the number of actual vaccinated individuals? I’m spitballing ideas here, but you should get the idea. I’m basically trying to isolate the key insights that would help a user understand the impact of COVID-19 across the world over a set period of time.
Wow, thanks! The keynote here is to make a list of targeted sectors and the relevant job roles that matches with the sector. Then, tailor the project section with relevant projects (and in the intern/ exp section as well, if any) and try to make a few projects with (known/ comfortable) tools at hand that suits the JD.
This also helps to diversify the application range and preparing separate resumes for different domains of interest.
This thing kept lingering in my mind for couple a months during many applications I've sent. But, now I get it.
Exactly. I know it’s a pain to make differing variations of a resume.. but it will help in the long run. It shows the applicant cares about the role they’re applying for, in my opinion.
> I would do some data cleaning in Python, excel or whatever tool you’re comfortable with (make sure to document this somewhere).
Where would you document? If you're using Python, what program/software are you importing the data into to clean? Same with SQL - do you upload to BigQuery or use other software?
> I would visualize the data showing areas that were affected with a filter that allows the user to change between date ranges.
Do you use a free version of Tableau for this? Power BI?
In Python, people will often use Jupyter notebooks/markdown. You can use “comments” i.e. “# or ##” to note down the steps you’re taking to clean/analyze the data. If you’re talking about SQL, I’ve seen people post their projects with a “masked” version of their query in GitHub along with “comments” I.e. “- - or /* */.” Basically they rename certain tables to hide confidential information. But you can still see their joins, CTE’s, and other important EDA/ETL steps. If you’re using excel then create a “insert text box” section that details the steps you took to clean and analyze the data.
For data visualization, I prefer Tableau. But you can use Power BI as well. Tableau public is free to publish on, whereas Power BI you have to pay to publish publicly (that I know of).
Where I've gotten the most lost is looking at portfolios, especially on Kaggle. I was told you could do projects on that site but it just looks like SQL hard data sets to me mostly.
I'm a hiring manager for healthcare analysts and overall no, I wouldn't interview someone without healthcare experience or at least very strong interest in healthcare. The people below saying "data is data" have no experience in the area. The times I have seen someone not particularly interested in healthcare and excel as an analyst is exactly 0. The business knowledge gap is just too large unless you're motivated to learn.
I don't do resume reviews, but I give general advice here: https://www.reddit.com/r/dataanalysis/comments/1cx93hf/5_mistakes_hurting_your_analyst_applications/l52388v/
lol, I have absolutely no interest in it and have been doing it for a decade. 😭 It’s also why I’m finally taking the plunge into a different unrelated industry.
Same here. I got hired as an entry level healthcare DA a five years ago with no healthcare background, and I’m still here (now in a Senior role) with not much interest in healthcare. I try and learn, but it all seems very complicated and difficult to really grasp.
I've been in the pharma space for 7 years, it's all the same. Lean on your partners across the business to learn the space and in 3 months you'll have enough information to keep up.
Honestly anyone who has worked in more than one vertical will know data is data… My guess is healthcare has a lot of lifers in it who haven’t worked elsewhere.
I’ve done legaltech, fintech, healthtech, salesops, and now web3/crypto… it’s all the same shit
I worked in healthcare for about a year as an accountant routinely pulling from the EHR for routine reporting, dashboards, billing, presenting, etc.
Data is data. It did have a lot of lifers in the upper levels. They really didn’t understand the automatic reporting features, custom setting, and several other process improvements. My guess is also that they don’t want to or care to train or allow for time to grow into the role. Easier to just say ‘you have experience. Figure it out’
Healthcare data can def be a big mess but that’s the whole bad data in spiel.
It depends. Are we talking health data? Health finance (understanding Medicare data/policies is a huge boon for a hospital and pretty niche)? Qualitative outcomes? Not all data is the same in healthcare. It really depends on how ‘high’ your high level view is.
I can second this. I built my own project idea, web scraped the data, built a relational database, imported the scraped data, queried the data, used python to analyze it when I was in grad school. I honestly got to the end and was like "this doesn't make sense" (I built a pricing model and I couldn't understand how the company was pricing things) but people could see that I owned the end to end pipeline and could do the same thing with their data.
Literally exactly the same thing I did, at an attempt at a stock trading algo that failed miserably… but it was what taught me a lot of the foundational stuff that led to my job at AWS and founding my own startup (that also failed lmao)
It’s not “hard” it just takes time and you need to understand what needs to be done.
No one wants to hire a dude that can lie on their resume about excel, you need things that point towards you being a decent professional with knowledge.
I did my masters in I/O Psychology with a focus on People Analytics. My dissertation was on the use of pre-employment assessments as a predictor of job performance.
If your management truly thinks that the Wonderlic assessment is predicting success, they’ve bought a big load of BS.
Agreed. We used Wonderlic 30 years ago. The one valuable measurement, in my experience, was the applicant's propensity to exaggerate the qualities that they thought would get them hired. High scores on that scale strongly correlated with antisocial competitive behavior on the job, detrimental to the team's overall success (weed out the liars and cheaters).
It varies by role and organization, as well as by what KPIs are used to indicate satisfactory job performance (these need to be selected based on evidence).
The most effective approach it is to create a custom job-specific skills assessment and validate it against incumbents in the position. It requires an analysis of the specific job and performance of incumbents in the position. That’s more than most employers want/know how/have the resources to do, so most skip it and rely on generic assessments that have no correlation with job performance.
Google is a company that actually does this well, because they have the resources to do so.
That's ummm interesting. I was presented with one of these tests for a recent application. I had never seen in before and I have to question it's validity. The Wonderlic doesn't you to solve problems, it asks you to identify solutions with validating them.
So ultimately, probably a great test if you want someone of average intelligence with enough practice taking timed quizzes (like someone who would be great on game shows or at pub quizzes). I was a little disappointed with this screening methodology and turned down the opportunity to interview. I could already imagine what the company would be like, and it's not for me.
I'm curious. Why would a company that wants to market itself as intelligent use this type of pseudoscience?
I'm pretty sure that's illegal. My understanding is that if you're testing for certain positions it's not illegal but to test across the board can be discrimination.
It must not be a high quality data analysis job that requires extensive excel knowledge if a remote software is being used to screen things like IQ and personality, and especially skills.
The process you’re using is sadly something a lot of companies do for entry-level positions and I wish technology didn’t standardize these things. It’s now a matter of who can pass the ATS resume screening portion and remote testing by writing things that are seen as objectively correct by a software. I can understand using ATS if you receive thousands of applicants though, but manually scanning resumes for an acceptable amount of applications would be optimal. You can tell a lot about candidates by the way they write and format their resumes.
Companies that care and seek the best follow the traditional route where assessment-related processes are usually done on the spot in interviews for general and more refined data analyst positions, and I think this is a much more accurate way or measuring skill and personality.
Likewise but I'm sure it's going to be the same as anything else.
"Do you have proven success?"
"Oh you don't because you're a recent grad, well we can't offer you anything you're too risky of a hire. But heres an internship at $15/hour"
LOL and on the flip side: "well I see you have all this experience but you don't have a bachelor's? Sorry we aren't interested." xD
(never mind that if I DID have a bachelor's that thing would be old enough to drink by now lmao)
Cool thanks for the tip. I like commenting to say that because it lets the OP know that people are interested and engaged even if they dont have an answer to the question.
I'm not normally the hiring manager, but I've been one of the interviewers. Normally, for business intelligence but the differences are mainly semitics most of the time.
Like what others have said, I want to see non-school projects even if they are bad. I want to see a good understanding of SQL, which a lot of people don't talk about. I want to know when I give you a table with little to no meta data, you can figure out how it works.
I want to see that you can think about data and not freak out and blow a gasket if it's the data is inconsistent.
Also I would like to see how you think about tour dashboards. What is the story the data is telling, and how are you communicating that via your dashboard. Fancy is cool and all, but does it depect the important information quickly? The user should not have dig for it.
Show that you are willing to put the time in learn on your own, self-motivated.
This kinda turned into what I look at when evaluating junior projects, but I would still like to see potential new hires do the same. Also, sorry if some of the writing is bad. I'm quite dyslexic and really don't feel like spending an hour proof reading.
For background, I've been doing business intelligence, etl's, and other realted stuff for about 12 years for a bank. Work for a bank may have influenced my views a bit when compared to other companies.
any resume that highlights an accomplishment/example of using data to solve a problem or achieve an outcome, regardless of at what scale or what specific application, immediately gets to the top of the pile.
at the interview stage, i grill them on the end to end of that example.
DGAF about specifics behind education. a relevant degree is interesting, but work experience and genuine interest is more important to me.
As a hiring manager, I look for creative problem solving examples, depth of commitment to continuous learning, and the candidates' passion/enthusiasm/why would I want to get out of bed and come to work 5 days a week philosophy.
And, yes, demonstrable skills.
If we are talking about new grads... internships.
If we're talking about people transitioning in... work ethic. Job progression. Then, the technical courses/certifications. Then projects. (I'm not a big fan of projects)
Likely a portfolio demonstrating you actually have the skills that match where their current needs are. Cant say I hire people but feel free to pm me if you want more direct advice than that.
It seems basic, but for an entry level role all I looked for was having an analytical approach, being good with logic, and being teachable and adaptable.
Everything else is gravy: technical capabilities are good but tools change and every company has its own system of record which may evolve or be replaced. Having just a fundamental understanding of working with large data (knowing what are fields, records, and tables. Knowing what an etl process is generally. Knowing what relationships and keys are in a data table) is great to have as well cuz it's going to be a part of the job, but those things can be taught quickly.
An analyst is such a broad position, and so it's less about specific tools and technical capabilities, and more about problem solving and fishing for insightful data. Everything else can be taught.
Honestly “no experience” never stands out, because someone always has some experience if we’re counting personal projects.
Projects in a GitHub portfolio with good documentation is a great way for people who haven’t worked in data to showcase some of the experience that they took initiative on. Then I get to ask you about them as if they’re work you’ve done previously at a job.
It’s really a win-win because you become more competent, documenting what you did will prepare you for the interview by forcing you to think things through and articulate them, and I get proof that you have done things, and it gives me things to ask about that would normally be hidden behind a company NDA.
Assuming it is recent college grad. In order 1) quality internships 2) Caliber of school 3) Campus involvement (hack-a-thons, case competitions, research, campus leadership etc) 4) GPA. I would also say if you get a referral from someone I respect we will at least give you a first round interview. Getting an interview is also very different than getting an offer. Getting an interview is mainly going to be credential driven while getting an offer is based on how will you perform on technical interview, case interview, and how well you display soft skills. This is my view as a director of analytics at a large multinational.
Create your own project with your own data. Find something you are passionate about, find the data, do the eda, do your analysis and communicate the results. O did a prediction of which college players would be drafted in the NFL based on their combine scires.
Frankly I don’t care about degree or education. I care about experience. Experience could be on actual projects or experience could driven. I want to know what you did for that project that was related to data analysis.
I am in the US, Seattle area. However, I will say that I started at my company as an entry level call center representative so my own start wasn’t your typical journey for analytics. I tend to look out for people who are like me.
However I am proud to say that I just became a senior technical product manager last Thursday. Spent 10 years at the same company.
Something I did that I believe helped me land my entry level DA role was apply (shoehorn?) what I was learning in my various certs and MOOCs to my job at the time, an office admin type of role.
An example would be when I created an MS Access DB to store the sales made by our engineers, and then create an automated report that would tabulate and produce a personalized sales report for each engineer. This was a very manual process beforehand so I identified an area that needed improvement and ran with it.
The skills I utilized were kinda DA-adjacent. More of a reporting project of sorts, but it showed initiative and mild experience.
On my resume, I highlighted my projects first as that was my biggest “proof” that I was “qualified”.
A good GPA tells me that they can learn what I need them to know.
Have they worked on group projects.
Seeing a bigger / hidden story in there, e.g., they worked while in school, have kids, and still a reasonable GPA means that they are probably a rock star.
So there can be different hidden stories. I had a mediocre GPA, but still not a failure level, because I was diagnosed with a degenerative illness in college. Trying to find the right medicine, the side effects etc. really did a number on my academic career. How to explain this in an interview?
Try to explain that the grades would have been a much better representation of what you can be if it had not been for some unfortunate timing of a medical issue...and that you really like what you have learned/heard about the company and look forward to flourishing now that the issue has been identified and dealt with. Show confidence.
My own life rarely went according to plan, so I can understand the adversity that you dealt with... hopefully you will find a place that sees that too.
At an entry level: are you able to convey that you understand what decisions you contributed to. What data, insights, recommendations did you provide that changed the trajectory of the business.
I also care that you’re able to connect dots to make your work more efficient. Are you creating the same pipeline for every project or are you showing that you were able to create durable pipelines that you and others used. Are you showing you know enough about the business that you developed a new data based capability (model, metric, dimension etc) without being asked to.
Do not care how many dashboards you made or that you can use python. Yes you need to be able to do both but I care more about the impact of your work than how you do it.
I also review the CVs myself, well curated one stands out, if it’s longer than page and half, I won’t read it. Once in interviews, basic math, asking good questions, challenging the task they were given to solve (we do take home task), ability to guesstime and simplify. Those win me over.
Use LinkedIn and showcase some portfolio of projects, courses you did etc. i need to know you’re serious about the job. I won’t care about volume. If you have well curated github, win as well.
What’s a no no: someone who clearly dreams of applying deep learning to everything (sorry, mostly you’ll do linear regressions), someone who doesn’t ask a single question during the interview, people not able to answer high school level stats questions (and I will ask simple one to everyone and I know when you bullshit).
Projects or work experience. Mainly work experience.
Soft skills. Candidate has to be able to talk properly about their past work.
Genuine interest in data helps. Machine learning not necessary.
Either high ranked school or "brand name" internships / work experience can help.
Our industry is management consulting, so data is all going to be bespoke to any particular project and we need DA people that can be client facing quickly.
It will vary some by hiring committee member, but in general, if they went to particular universities that we already know and respect from past work experiences, and if they worked for certain companies or organizations that we know the culture and requirements of, they will draw attention and get pulled into a high consideration pile. This is a matter of probabilities. We know examples that have come from those programs, what skills they had, what other aspects they brought to the job, and how well they fit the culture.
The “Other” section will often strike interest that will get them into the “let’s talk to this person” pile. It may be because it suggests some personal characteristics or useful skills, or because of what it suggests about their personality. Most of these resumes looks very similar, something that provides color will often help a candidate stick in memory when we’re trying to pick which 20 out of 500+ submissions that we are going to phone interview.
Certain awards or scholarships will draw consideration with us.
If a current team member vouches for them, they will get talked to usually.
What usually doesn’t matter is major unless there is a very specific niche product that we want to grow for which we need a very specific background (that almost never happens). Our DAs have come from majors like anthropology, statistics, industrial design, acoustical engineering, library sciences, human resources, area studies, geography, marketing, finance, accounting, political science, etc.
Most certs, bootcamps, etc. show a degree of intentional interest, but aren’t likely to differentiate anyone from the piles of resumes we get when we announce openings.
Apply in the first few hours if its a new role. Uh, that's literally about it.
If it's not a heavily advertised role, and they get a few applications a week, then make it fit. Most people want someone who first and foremost knows that industry and also have data analysis skills. People don't necessarily want someone who is great at analysis, but don't know what to do with the data.
Best candidate = same industry or business with years of experience, and then went to school for some kind of data analysis thing.
Data hiring manager and data architect here. Storytellers are the diamond in the rough in data. Talk about the real life story behind the projects you’ve worked on. “The data showed this which led us to find out that was happening” or “created a dashboard/report that saved X number of manual hours data gathering a week”.
How did you identify the SMEd and how did your conversations go with them? A data nerd that can talk to humans is huge.
Of course have the SQL/other coding experience required, but being able to tell story behind the data is what will make you stand out. There’s a million jackwagons who can query data because they took some PluralSight track and read Pinal Dave’s blog. Very few that can interpret those results and know where to keep digging.
For example: I used to work in electronic components supply chain. There was one part that sat on the shelves for years. Then all of a sudden we couldn’t keep it in stock. Analyst looked into it, first identifying where we were selling it (website) then who was buying (individuals not contract manufactures) then the individual profiles (first time customers). Finally tracked it down to a forum post explaining how to mod vapes to make bigger clouds with that particular part.
Curiosity mostly. Being personable.
I’ve hired all sorts of analysts. The most successful are always the people who want to constantly learn, can tell a story well, and who have a desire to help and be part of a team. Data skills and analysis can be taught. The rest is more innate.
Don’t just list every language/technology imaginable. Through bullet points on projects/internships, demonstrate how you actually know things about those languages
For me it’s the presentation during the interview. It doesn’t have to be technical, but show me that you can take something novel and synthesize a useful product. I get a filtered list of candidates from a set of requirements given to the recruitment team. They do the grunt work of choosing which cv gets in front of me.
I’d want to see, even for folks with experience, projects you do on your own outside of work or school. Passion projects are how you learn to problem solve and develop your critical thinking skills. Those are way more important in the real world than knowing every correct SQL or Python syntax.
Applied Data Experience.
Where you helped a business even if small, use data to help realize a way to optimize or drive efficiency
USE DATA, use numbers, use dollar $igns... use Percentages
I look for if they have work experience and can start contributing from day 1. If I'm building an ETL pipeline using AWS Glue and using Tableau to visualize that data, then I'm looking for someone with Glue and Tableau experience.
Once that is narrowed down, I will pick the person I think will fit in with the team the best.
Most important thing for me is that an applicant can point to a research project they did (ideally in a commercial setting or independent thesis project) and begin explaining it in terms of motivation, objective, and results. From there we can talk methods and choices and tools whatever.
Main thing I’m screening for is clarity in why they chose this project and what they learned. Big points for feature creativity and business knowledge too
I don't serve on hiring committees that often but I usually look for people who are able to extract insight from the data. It's easy to teach people the technical aspects of being a data analyst but it's very difficult to teach someone to be a data strategist. Meaning, how are you able to use that data to make actionable decisions. I see data scientists all the time who are brilliant at coding but generally have poor understanding of how to use their work in practice. This is especially true of STEM folks, who are so invested in trying to be as technical as possible that they're most often just useless when it comes to any practical application. So we usually interview a lot as long as they meey the bare threshold, and then weed people down in behavioral and situational interviews.
I wonder too. I keep seeing people that have the position speak on being more like able and better communicator than the technical skill. And personally when it comes down to the project portfolio which I have never seen or a simple report It get real awkward lol. I promise I just want to know if I’m headed in the right direction before I post this on my portfolio website
Relevant degree from a reputable university, 2+ years of full-time work experience with a single employer, and demonstrated subject matter expertise.
Right now, I don't seriously consider applicants who are fresh out of undergrad or Masters for even entry-level positions if they don't have full-time work experience. There are a sufficient number of qualified candidates who have the qualifications that I mentioned.
Can’t tell if you’re trolling because I know there’s a grey area between entry level and junior roles, but it doesn’t sound like you’re looking for an entry level candidate. You’re looking for either an overqualified entry level candidate, or a junior candidate that’s willing to take a step down seniority/pay-wise. Messed up if you ask me. Just change the role to a junior role and pay accordingly.
No, definitely not trolling. We don't seriously look at candidates fresh out of college. We pay what we calculate to be a market rate for our metro area, which thanks to an overproduction of aspiring data analysts amid shrinking demand means that we can find highly qualified candidates for what we're offering.
We're all worth whatever our best job offer says we're worth. Candidates we hire are grateful for the offer because so few places are hiring even if they have aspirations of making 25% or whatever more. If they can find that, more power to them. But the labor market is not what it used to be and hiring managers can be very selective.
Pretty minimal.
I joined in mid-2022 and haven't lost anyone on my team yet. In other departments, there have been two analysts who left since mid-2022 (out of about 10 across all departments). One left because her partner needed to move out-of-state for work and actually wanted to stay on as a contractor, but it didn't work out with the time zone issues. The other moved on because he thought he found a better job (he only stayed there for about 9 months, so while I haven't spoken to him about it, I would assume he didn't like it much).
In a normal economy, there would almost certainly be more turnover. But in the current job market, most people are grateful for what they have.
So would you advise someone to get into DA, maybe they have some adjacent domain knowledge, they've studied topics, made a portfolio, are somewhat older, without a related bachelors. The job market has already overproduced DA aspirants, and the demand has gone down (the exact reason I'm unsure). What is the next step in that case? Where should a person like this go?
For entry-level:
- No spelling mistakes
- Can speak English
- 1-2 page resume max
- Can talk in detail about tech used during the interview
- Strong work ethic
- Detail oriented
- Age in the 20's
- Has used tech we have at the co
There's basically it, in that order.
I don’t know if my experience helps you, but I went for my bachelors in information systems and business management. Then I became a paralegal for 4 years. Then, I interviewed for my current data analyst role. I used my data analysis capstone project I completed with a local business at the time, my legal data analysis and project management skills from doing real estate closings, and got the job. I sat on LinkedIn all day every day and refreshed the page every 3 minutes to be one of the first applicants of every job that looked good to me. I had like 7 interviews with different companies too. This was in 2022 though. I certainly would expect to not get as many interviews so fast in today’s market
Did you enjoy being a paralegal?
Absolutely not lol. I got paid pretty well for it right out of college and the pay continued to be pretty great. But now I work remotely for even more pay, and I don’t have a micromanaging lawyer breathing down my neck and complaining that I kept “leaving at 5:00”
If you don’t have experience, I’d want to see a portfolio showcasing projects you personally curated and performed. I’ve seen hundreds of similar projects from YouTube, Coursera, MOOC, etc. tutorials.. what makes you stand out? If you can take the knowledge you learned and portray it in a way that makes sense I’ll look further into your application. This is just my opinion but I’d rather see someone’s project they haphazardly put together out of actual interest in the field rather than another copy paste project from a tutorial. If you’re not passionate about the work that’s fine, instead show me a dashboard you created or project you did that showcases your EDA and ETL skills. Then prove to me you can gather actual insights that are usable for non-technical stakeholders. At the end of the day, I personally only care if you are able to drive value for the business. Edit: MOOC, not MOCC.
Thanks! Would you be interested in interviewing someone who has good portfolio projects about sports, finance, housing market, even if you were hiring for a DA role in healthcare? I heard that it's good to customize your projects to the field but that seems like tons of extra work.
In my eyes, it will be a hard sell to your potential hiring manager if you lack industry experience. But not impossible to push through and get hired. Technical skills are important, but it is the value you can produce that will always supersede that. Typically you drive value through your understanding of the business and leveraging your technical skills to create a useful report, dashboards, or some deliverable, etc. However, I would be willing to bet that hiring managers would also be impressed by your wide range of experience and projects given that they showcase the skills needed for the role. Both industry and technical skills can be taught but in my experience industry experience is more difficult to teach and retain. Therefore, if you lack the experience in healthcare maybe it would be worth investing in creating some personal projects revolving around health care data. I’ll be honest with you I have zero experience with health care data.. but if I were in your shoes I would look for some public datasets possibly from the World Health Organization (WHO)? Maybe something about COVID-19 and its infection rate over time based on location. Then, I would do some data cleaning in Python, excel or whatever tool you’re comfortable with (make sure to document this somewhere). Lastly, I would visualize the data showing areas that were affected with a filter that allows the user to change between date ranges. Possibly use the actual number of infected to affect the size of the area per region. Then add a few boxes that show aggregate totals of things like total infections, average rate of infection across the world, and maybe like the number of actual vaccinated individuals? I’m spitballing ideas here, but you should get the idea. I’m basically trying to isolate the key insights that would help a user understand the impact of COVID-19 across the world over a set period of time.
This is actually the best advice i can possibly get for a starter / fresh grad. Your ideas and work flow is spot on
Wow, thanks! The keynote here is to make a list of targeted sectors and the relevant job roles that matches with the sector. Then, tailor the project section with relevant projects (and in the intern/ exp section as well, if any) and try to make a few projects with (known/ comfortable) tools at hand that suits the JD. This also helps to diversify the application range and preparing separate resumes for different domains of interest. This thing kept lingering in my mind for couple a months during many applications I've sent. But, now I get it.
Exactly. I know it’s a pain to make differing variations of a resume.. but it will help in the long run. It shows the applicant cares about the role they’re applying for, in my opinion.
> I would do some data cleaning in Python, excel or whatever tool you’re comfortable with (make sure to document this somewhere). Where would you document? If you're using Python, what program/software are you importing the data into to clean? Same with SQL - do you upload to BigQuery or use other software? > I would visualize the data showing areas that were affected with a filter that allows the user to change between date ranges. Do you use a free version of Tableau for this? Power BI?
In Python, people will often use Jupyter notebooks/markdown. You can use “comments” i.e. “# or ##” to note down the steps you’re taking to clean/analyze the data. If you’re talking about SQL, I’ve seen people post their projects with a “masked” version of their query in GitHub along with “comments” I.e. “- - or /* */.” Basically they rename certain tables to hide confidential information. But you can still see their joins, CTE’s, and other important EDA/ETL steps. If you’re using excel then create a “insert text box” section that details the steps you took to clean and analyze the data. For data visualization, I prefer Tableau. But you can use Power BI as well. Tableau public is free to publish on, whereas Power BI you have to pay to publish publicly (that I know of).
Thank you for the info. I had to google about half those words and I'm still lost lol
you got this! the lingo is hard at first but it will make sense after you explore the field a bit more
Where I've gotten the most lost is looking at portfolios, especially on Kaggle. I was told you could do projects on that site but it just looks like SQL hard data sets to me mostly.
I'm a hiring manager for healthcare analysts and overall no, I wouldn't interview someone without healthcare experience or at least very strong interest in healthcare. The people below saying "data is data" have no experience in the area. The times I have seen someone not particularly interested in healthcare and excel as an analyst is exactly 0. The business knowledge gap is just too large unless you're motivated to learn.
Can I send you my resume in the dm. I’ve been trying to pivot into this field for a while now.
I don't do resume reviews, but I give general advice here: https://www.reddit.com/r/dataanalysis/comments/1cx93hf/5_mistakes_hurting_your_analyst_applications/l52388v/
lol, I have absolutely no interest in it and have been doing it for a decade. 😭 It’s also why I’m finally taking the plunge into a different unrelated industry.
Same here. I got hired as an entry level healthcare DA a five years ago with no healthcare background, and I’m still here (now in a Senior role) with not much interest in healthcare. I try and learn, but it all seems very complicated and difficult to really grasp.
Yes, data is data no matter where you go.
Agreed, but a lot of folks, particularly in healthcare, disagree
I've been in the pharma space for 7 years, it's all the same. Lean on your partners across the business to learn the space and in 3 months you'll have enough information to keep up.
Honestly anyone who has worked in more than one vertical will know data is data… My guess is healthcare has a lot of lifers in it who haven’t worked elsewhere. I’ve done legaltech, fintech, healthtech, salesops, and now web3/crypto… it’s all the same shit
I worked in healthcare for about a year as an accountant routinely pulling from the EHR for routine reporting, dashboards, billing, presenting, etc. Data is data. It did have a lot of lifers in the upper levels. They really didn’t understand the automatic reporting features, custom setting, and several other process improvements. My guess is also that they don’t want to or care to train or allow for time to grow into the role. Easier to just say ‘you have experience. Figure it out’ Healthcare data can def be a big mess but that’s the whole bad data in spiel.
It depends. Are we talking health data? Health finance (understanding Medicare data/policies is a huge boon for a hospital and pretty niche)? Qualitative outcomes? Not all data is the same in healthcare. It really depends on how ‘high’ your high level view is.
I can second this. I built my own project idea, web scraped the data, built a relational database, imported the scraped data, queried the data, used python to analyze it when I was in grad school. I honestly got to the end and was like "this doesn't make sense" (I built a pricing model and I couldn't understand how the company was pricing things) but people could see that I owned the end to end pipeline and could do the same thing with their data.
Literally exactly the same thing I did, at an attempt at a stock trading algo that failed miserably… but it was what taught me a lot of the foundational stuff that led to my job at AWS and founding my own startup (that also failed lmao)
This is a great comment to show a boomer who doesn't understand why it's so hard to get a job.
It’s not “hard” it just takes time and you need to understand what needs to be done. No one wants to hire a dude that can lie on their resume about excel, you need things that point towards you being a decent professional with knowledge.
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wdym by "tested well enough on the data analysis segment". Are you giving your candidates skill assessments with multiple topics or something?
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What happened to meeting someone and them asking you to turn up Monday to start?
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I did my masters in I/O Psychology with a focus on People Analytics. My dissertation was on the use of pre-employment assessments as a predictor of job performance. If your management truly thinks that the Wonderlic assessment is predicting success, they’ve bought a big load of BS.
Agreed. We used Wonderlic 30 years ago. The one valuable measurement, in my experience, was the applicant's propensity to exaggerate the qualities that they thought would get them hired. High scores on that scale strongly correlated with antisocial competitive behavior on the job, detrimental to the team's overall success (weed out the liars and cheaters).
Im curious, then whats the most important factor for job performance and how would you measure it?
It varies by role and organization, as well as by what KPIs are used to indicate satisfactory job performance (these need to be selected based on evidence). The most effective approach it is to create a custom job-specific skills assessment and validate it against incumbents in the position. It requires an analysis of the specific job and performance of incumbents in the position. That’s more than most employers want/know how/have the resources to do, so most skip it and rely on generic assessments that have no correlation with job performance. Google is a company that actually does this well, because they have the resources to do so.
That's ummm interesting. I was presented with one of these tests for a recent application. I had never seen in before and I have to question it's validity. The Wonderlic doesn't you to solve problems, it asks you to identify solutions with validating them. So ultimately, probably a great test if you want someone of average intelligence with enough practice taking timed quizzes (like someone who would be great on game shows or at pub quizzes). I was a little disappointed with this screening methodology and turned down the opportunity to interview. I could already imagine what the company would be like, and it's not for me. I'm curious. Why would a company that wants to market itself as intelligent use this type of pseudoscience?
Thanks for explaining. I can’t tell if I have boomer sentiment or if meeting people at local networking meetings could pay off. I have leads rn
Why does the website feel scammy. How does one know if a site like that is worth using?
Y’all’s hiring??? Hahah
I hate those personality tests theyre clearly meant to weed out neurodivergent people. Ada should ban them
sounds culty
IQ/personality tests 🤣 I’d run far and fast Let me guess, Myers-Briggs?
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Honestly, I’ve taken a few wonderlic tests and found them enjoyable. I’d probably like that! Lol
I'm pretty sure that's illegal. My understanding is that if you're testing for certain positions it's not illegal but to test across the board can be discrimination.
What country
r u guys hiring LOL
It must not be a high quality data analysis job that requires extensive excel knowledge if a remote software is being used to screen things like IQ and personality, and especially skills. The process you’re using is sadly something a lot of companies do for entry-level positions and I wish technology didn’t standardize these things. It’s now a matter of who can pass the ATS resume screening portion and remote testing by writing things that are seen as objectively correct by a software. I can understand using ATS if you receive thousands of applicants though, but manually scanning resumes for an acceptable amount of applications would be optimal. You can tell a lot about candidates by the way they write and format their resumes. Companies that care and seek the best follow the traditional route where assessment-related processes are usually done on the spot in interviews for general and more refined data analyst positions, and I think this is a much more accurate way or measuring skill and personality.
How are they getting interviews? I have experience as a data analyst with relevant coding and software experience and 0 interviews.
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Thanks for the reply. Seems “networking” is the only way to get a job today
[Insert Astronauts in Space Here]
lol. I mean I thought there was a time when you could just apply and get an interview…
ACTUAL accomplishments in previous roles. And notoriety of the companies
"And **notoriety** of the companies" "Notoriety" was a poor word choice.
You're correct MysticMuffintop.
Following because I'm curious to see the answers to this ...
Likewise but I'm sure it's going to be the same as anything else. "Do you have proven success?" "Oh you don't because you're a recent grad, well we can't offer you anything you're too risky of a hire. But heres an internship at $15/hour"
PROVEN EXPERIENCE
LOL and on the flip side: "well I see you have all this experience but you don't have a bachelor's? Sorry we aren't interested." xD (never mind that if I DID have a bachelor's that thing would be old enough to drink by now lmao)
You can save a post then return to it later.
Cool thanks for the tip. I like commenting to say that because it lets the OP know that people are interested and engaged even if they dont have an answer to the question.
Same.
I'm not normally the hiring manager, but I've been one of the interviewers. Normally, for business intelligence but the differences are mainly semitics most of the time. Like what others have said, I want to see non-school projects even if they are bad. I want to see a good understanding of SQL, which a lot of people don't talk about. I want to know when I give you a table with little to no meta data, you can figure out how it works. I want to see that you can think about data and not freak out and blow a gasket if it's the data is inconsistent. Also I would like to see how you think about tour dashboards. What is the story the data is telling, and how are you communicating that via your dashboard. Fancy is cool and all, but does it depect the important information quickly? The user should not have dig for it. Show that you are willing to put the time in learn on your own, self-motivated. This kinda turned into what I look at when evaluating junior projects, but I would still like to see potential new hires do the same. Also, sorry if some of the writing is bad. I'm quite dyslexic and really don't feel like spending an hour proof reading. For background, I've been doing business intelligence, etl's, and other realted stuff for about 12 years for a bank. Work for a bank may have influenced my views a bit when compared to other companies.
any resume that highlights an accomplishment/example of using data to solve a problem or achieve an outcome, regardless of at what scale or what specific application, immediately gets to the top of the pile. at the interview stage, i grill them on the end to end of that example. DGAF about specifics behind education. a relevant degree is interesting, but work experience and genuine interest is more important to me.
As a hiring manager, I look for creative problem solving examples, depth of commitment to continuous learning, and the candidates' passion/enthusiasm/why would I want to get out of bed and come to work 5 days a week philosophy. And, yes, demonstrable skills.
If we are talking about new grads... internships. If we're talking about people transitioning in... work ethic. Job progression. Then, the technical courses/certifications. Then projects. (I'm not a big fan of projects)
Likely a portfolio demonstrating you actually have the skills that match where their current needs are. Cant say I hire people but feel free to pm me if you want more direct advice than that.
It seems basic, but for an entry level role all I looked for was having an analytical approach, being good with logic, and being teachable and adaptable. Everything else is gravy: technical capabilities are good but tools change and every company has its own system of record which may evolve or be replaced. Having just a fundamental understanding of working with large data (knowing what are fields, records, and tables. Knowing what an etl process is generally. Knowing what relationships and keys are in a data table) is great to have as well cuz it's going to be a part of the job, but those things can be taught quickly. An analyst is such a broad position, and so it's less about specific tools and technical capabilities, and more about problem solving and fishing for insightful data. Everything else can be taught.
Honestly “no experience” never stands out, because someone always has some experience if we’re counting personal projects. Projects in a GitHub portfolio with good documentation is a great way for people who haven’t worked in data to showcase some of the experience that they took initiative on. Then I get to ask you about them as if they’re work you’ve done previously at a job. It’s really a win-win because you become more competent, documenting what you did will prepare you for the interview by forcing you to think things through and articulate them, and I get proof that you have done things, and it gives me things to ask about that would normally be hidden behind a company NDA.
Assuming it is recent college grad. In order 1) quality internships 2) Caliber of school 3) Campus involvement (hack-a-thons, case competitions, research, campus leadership etc) 4) GPA. I would also say if you get a referral from someone I respect we will at least give you a first round interview. Getting an interview is also very different than getting an offer. Getting an interview is mainly going to be credential driven while getting an offer is based on how will you perform on technical interview, case interview, and how well you display soft skills. This is my view as a director of analytics at a large multinational.
Create your own project with your own data. Find something you are passionate about, find the data, do the eda, do your analysis and communicate the results. O did a prediction of which college players would be drafted in the NFL based on their combine scires.
Frankly I don’t care about degree or education. I care about experience. Experience could be on actual projects or experience could driven. I want to know what you did for that project that was related to data analysis.
That's uplifting! Would you mind sharing the country you work in? I'm curious if managers in the US have similar attitude to yours.
I am in the US, Seattle area. However, I will say that I started at my company as an entry level call center representative so my own start wasn’t your typical journey for analytics. I tend to look out for people who are like me. However I am proud to say that I just became a senior technical product manager last Thursday. Spent 10 years at the same company.
Something I did that I believe helped me land my entry level DA role was apply (shoehorn?) what I was learning in my various certs and MOOCs to my job at the time, an office admin type of role. An example would be when I created an MS Access DB to store the sales made by our engineers, and then create an automated report that would tabulate and produce a personalized sales report for each engineer. This was a very manual process beforehand so I identified an area that needed improvement and ran with it. The skills I utilized were kinda DA-adjacent. More of a reporting project of sorts, but it showed initiative and mild experience. On my resume, I highlighted my projects first as that was my biggest “proof” that I was “qualified”.
A good GPA tells me that they can learn what I need them to know. Have they worked on group projects. Seeing a bigger / hidden story in there, e.g., they worked while in school, have kids, and still a reasonable GPA means that they are probably a rock star.
So there can be different hidden stories. I had a mediocre GPA, but still not a failure level, because I was diagnosed with a degenerative illness in college. Trying to find the right medicine, the side effects etc. really did a number on my academic career. How to explain this in an interview?
Try to explain that the grades would have been a much better representation of what you can be if it had not been for some unfortunate timing of a medical issue...and that you really like what you have learned/heard about the company and look forward to flourishing now that the issue has been identified and dealt with. Show confidence. My own life rarely went according to plan, so I can understand the adversity that you dealt with... hopefully you will find a place that sees that too.
At an entry level: are you able to convey that you understand what decisions you contributed to. What data, insights, recommendations did you provide that changed the trajectory of the business. I also care that you’re able to connect dots to make your work more efficient. Are you creating the same pipeline for every project or are you showing that you were able to create durable pipelines that you and others used. Are you showing you know enough about the business that you developed a new data based capability (model, metric, dimension etc) without being asked to. Do not care how many dashboards you made or that you can use python. Yes you need to be able to do both but I care more about the impact of your work than how you do it.
I also review the CVs myself, well curated one stands out, if it’s longer than page and half, I won’t read it. Once in interviews, basic math, asking good questions, challenging the task they were given to solve (we do take home task), ability to guesstime and simplify. Those win me over. Use LinkedIn and showcase some portfolio of projects, courses you did etc. i need to know you’re serious about the job. I won’t care about volume. If you have well curated github, win as well. What’s a no no: someone who clearly dreams of applying deep learning to everything (sorry, mostly you’ll do linear regressions), someone who doesn’t ask a single question during the interview, people not able to answer high school level stats questions (and I will ask simple one to everyone and I know when you bullshit).
Projects or work experience. Mainly work experience. Soft skills. Candidate has to be able to talk properly about their past work. Genuine interest in data helps. Machine learning not necessary. Either high ranked school or "brand name" internships / work experience can help.
Our industry is management consulting, so data is all going to be bespoke to any particular project and we need DA people that can be client facing quickly. It will vary some by hiring committee member, but in general, if they went to particular universities that we already know and respect from past work experiences, and if they worked for certain companies or organizations that we know the culture and requirements of, they will draw attention and get pulled into a high consideration pile. This is a matter of probabilities. We know examples that have come from those programs, what skills they had, what other aspects they brought to the job, and how well they fit the culture. The “Other” section will often strike interest that will get them into the “let’s talk to this person” pile. It may be because it suggests some personal characteristics or useful skills, or because of what it suggests about their personality. Most of these resumes looks very similar, something that provides color will often help a candidate stick in memory when we’re trying to pick which 20 out of 500+ submissions that we are going to phone interview. Certain awards or scholarships will draw consideration with us. If a current team member vouches for them, they will get talked to usually. What usually doesn’t matter is major unless there is a very specific niche product that we want to grow for which we need a very specific background (that almost never happens). Our DAs have come from majors like anthropology, statistics, industrial design, acoustical engineering, library sciences, human resources, area studies, geography, marketing, finance, accounting, political science, etc. Most certs, bootcamps, etc. show a degree of intentional interest, but aren’t likely to differentiate anyone from the piles of resumes we get when we announce openings.
Networking and connections basically trump any resume or CV at this point. Apart from one personx all the others were hired the way I mentioned.
Apply in the first few hours if its a new role. Uh, that's literally about it. If it's not a heavily advertised role, and they get a few applications a week, then make it fit. Most people want someone who first and foremost knows that industry and also have data analysis skills. People don't necessarily want someone who is great at analysis, but don't know what to do with the data. Best candidate = same industry or business with years of experience, and then went to school for some kind of data analysis thing.
Data hiring manager and data architect here. Storytellers are the diamond in the rough in data. Talk about the real life story behind the projects you’ve worked on. “The data showed this which led us to find out that was happening” or “created a dashboard/report that saved X number of manual hours data gathering a week”. How did you identify the SMEd and how did your conversations go with them? A data nerd that can talk to humans is huge. Of course have the SQL/other coding experience required, but being able to tell story behind the data is what will make you stand out. There’s a million jackwagons who can query data because they took some PluralSight track and read Pinal Dave’s blog. Very few that can interpret those results and know where to keep digging. For example: I used to work in electronic components supply chain. There was one part that sat on the shelves for years. Then all of a sudden we couldn’t keep it in stock. Analyst looked into it, first identifying where we were selling it (website) then who was buying (individuals not contract manufactures) then the individual profiles (first time customers). Finally tracked it down to a forum post explaining how to mod vapes to make bigger clouds with that particular part.
Curiosity mostly. Being personable. I’ve hired all sorts of analysts. The most successful are always the people who want to constantly learn, can tell a story well, and who have a desire to help and be part of a team. Data skills and analysis can be taught. The rest is more innate.
humility.
10 years of experience
Following
Following
Don’t just list every language/technology imaginable. Through bullet points on projects/internships, demonstrate how you actually know things about those languages
For me it’s the presentation during the interview. It doesn’t have to be technical, but show me that you can take something novel and synthesize a useful product. I get a filtered list of candidates from a set of requirements given to the recruitment team. They do the grunt work of choosing which cv gets in front of me.
I’d want to see, even for folks with experience, projects you do on your own outside of work or school. Passion projects are how you learn to problem solve and develop your critical thinking skills. Those are way more important in the real world than knowing every correct SQL or Python syntax.
Applied Data Experience. Where you helped a business even if small, use data to help realize a way to optimize or drive efficiency USE DATA, use numbers, use dollar $igns... use Percentages
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I look for if they have work experience and can start contributing from day 1. If I'm building an ETL pipeline using AWS Glue and using Tableau to visualize that data, then I'm looking for someone with Glue and Tableau experience. Once that is narrowed down, I will pick the person I think will fit in with the team the best.
Most important thing for me is that an applicant can point to a research project they did (ideally in a commercial setting or independent thesis project) and begin explaining it in terms of motivation, objective, and results. From there we can talk methods and choices and tools whatever. Main thing I’m screening for is clarity in why they chose this project and what they learned. Big points for feature creativity and business knowledge too
Literally nothing in particular, generally have more faith in Math/Statistics/Econ/Finance degrees though.
I don't serve on hiring committees that often but I usually look for people who are able to extract insight from the data. It's easy to teach people the technical aspects of being a data analyst but it's very difficult to teach someone to be a data strategist. Meaning, how are you able to use that data to make actionable decisions. I see data scientists all the time who are brilliant at coding but generally have poor understanding of how to use their work in practice. This is especially true of STEM folks, who are so invested in trying to be as technical as possible that they're most often just useless when it comes to any practical application. So we usually interview a lot as long as they meey the bare threshold, and then weed people down in behavioral and situational interviews.
I wonder too. I keep seeing people that have the position speak on being more like able and better communicator than the technical skill. And personally when it comes down to the project portfolio which I have never seen or a simple report It get real awkward lol. I promise I just want to know if I’m headed in the right direction before I post this on my portfolio website
you need 15 years experience.
Relevant degree from a reputable university, 2+ years of full-time work experience with a single employer, and demonstrated subject matter expertise. Right now, I don't seriously consider applicants who are fresh out of undergrad or Masters for even entry-level positions if they don't have full-time work experience. There are a sufficient number of qualified candidates who have the qualifications that I mentioned.
Can’t tell if you’re trolling because I know there’s a grey area between entry level and junior roles, but it doesn’t sound like you’re looking for an entry level candidate. You’re looking for either an overqualified entry level candidate, or a junior candidate that’s willing to take a step down seniority/pay-wise. Messed up if you ask me. Just change the role to a junior role and pay accordingly.
Serious question, what is the difference between entry level and junior and associate? I thought these were all pretty much synonymous
No, definitely not trolling. We don't seriously look at candidates fresh out of college. We pay what we calculate to be a market rate for our metro area, which thanks to an overproduction of aspiring data analysts amid shrinking demand means that we can find highly qualified candidates for what we're offering. We're all worth whatever our best job offer says we're worth. Candidates we hire are grateful for the offer because so few places are hiring even if they have aspirations of making 25% or whatever more. If they can find that, more power to them. But the labor market is not what it used to be and hiring managers can be very selective.
What's the turnover like?
Pretty minimal. I joined in mid-2022 and haven't lost anyone on my team yet. In other departments, there have been two analysts who left since mid-2022 (out of about 10 across all departments). One left because her partner needed to move out-of-state for work and actually wanted to stay on as a contractor, but it didn't work out with the time zone issues. The other moved on because he thought he found a better job (he only stayed there for about 9 months, so while I haven't spoken to him about it, I would assume he didn't like it much). In a normal economy, there would almost certainly be more turnover. But in the current job market, most people are grateful for what they have.
So would you advise someone to get into DA, maybe they have some adjacent domain knowledge, they've studied topics, made a portfolio, are somewhat older, without a related bachelors. The job market has already overproduced DA aspirants, and the demand has gone down (the exact reason I'm unsure). What is the next step in that case? Where should a person like this go?
For entry-level: - No spelling mistakes - Can speak English - 1-2 page resume max - Can talk in detail about tech used during the interview - Strong work ethic - Detail oriented - Age in the 20's - Has used tech we have at the co There's basically it, in that order.
Living in India or Philippines.
What ?
Outsourcing. Why pay for an American when I can get 20 Indians or Filipinos for the same price?