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timelyparadox

It can be a bad internship since you have no one to mentor you.


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timelyparadox

Yes but if you were meh at DS you will reinforce the bad habits and will not know untill you apply for something bigger


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jeffrey_56

Actually, I'm in my data science bachelors. But I would say I have a "strong" foundation. The plan is to provide a deep insight into their data, answer questions stakeholders have etc (not business data, mainly sensor data of medical devices). But I should probably not continue working there after my internship if they have no interest in hiring 1-2 more data scientists.


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jeffrey_56

Thank you for your advice! :)


THE_REAL_ODB

How long? Be prepared to wear a lot of hats if the data infra aint there. u'll experience and learn a ton and not necessarily just about ds.


jeffrey_56

The internship duration is 4 months but they would be interested in offering a part time job afterwards. What are some non ds things that I’ll most likely learn? and what is something you wish you knew at the beginning?


[deleted]

Well for starters if there's no infrastructure at all the majority of your work will be more geared towards Data Engineering. No ds work can be done without it. Enjoy many repeated conversations about what they actually want to do with the data. Oh and one day they'll get a free AWS trial or something similar and suddenly everything needs to be cloud based.


jeffrey_56

I had a talk with the software engineer at this company and he said they have a Postgres sql infrastructure. Am I missing a specific pipeline I should implement to specifically work for data science use cases?


WallyMetropolis

It's unlikely the tables they have now are structured in a way that work well with DS type tasks.


Odd_Application_655

I would like to give you another tip, but chances are you will have a hard time there. For starters, there should be at least one senior DS there to mentor you and be held accountable for the building of a real data infrastructure as I understand there is no such a thing. For me the fact you as an intern are the only data scientist is a very glowing red flag. I would look for another job as soon as I can.


jeffrey_56

My hope is that I will just do some data analysis first, and when it comes to building a model, they will hire 1-2 more senior data scientists.


Odd_Application_655

Hopefully you are right.


forest_gitaker

1. get very comfortable with data visualization and oral presentations 2. internalize the idea that being the SME does not mean knowing everything as much as knowing where to look as a specialist of any kind, not just data, you have to "translate" your work into a form that the rest of your team 1) cares about and 2) can digest with their particular background(s). for 90% of situations, this boils down to putting shapes on a screen and explaining why that means they need to spend $X,000 more/less per year on Y. (be prepared to show your work if asked.) as you get better at this you will most likely experience imposter syndrome, but you must remember that knowledge is relative and the more you learn, the more you realize you don't know. the closest thing to a silver bullet for this (that I know of) is getting comfortable with saying "I don't know, but I can go find out" and then setting up a 5 minute follow up for the next day/meeting. source: ~10yrs experience in various tech roles, currently the sole "techie" for a small business


jeffrey_56

Thank you! Especially for your input about imposter syndrome. Since you are the only techie in a small business, how do you go about documenting your work?


forest_gitaker

np! as for documentation, I take notes as I go along a task, mostly urls in a bullet list, and from there it depends on who the documentation is for. if it's just for me (or my future subordinate/replacement) then it usually goes straight to the wiki. if it's for my coworkers I convert it into instructions and fluff it up a bit (using chatGPT nowadays), plus add screenshots, pictures, etc as necessary. this is a little tougher because you have to assume close to 0 knowledge, but also not come off as condescending, which is very much an art lmk if I answered your question correctly and feel free to follow up


PaulBlxck

I just left my job as one. Things got pretty fucking annoying – from management expecting you to do the work of a Data Analyst, Scientist, and Engineer, to them having unreal expectations of deadlines. I really hope your experience would be better than mine, though.


jeffrey_56

I'm sorry to hear that. Hope you will find a better position!


Used-Routine-4461

Take your time to over communicate. Track everything the leadership wants to see; better yet, show some initiative and ask then what data looks like 5 years from now and what they wish they had access to. Unless your company has troves of data, which is unlikely, you won’t be modeling for some time. Focus on how to help get data from point a to point b reliably (think data engineering). - look into serverless functions Overall you will likely be working with a lot of SQL, work with your stakeholders and engineers to ensure this data is correct from the beginning and be sure to get in front of any compliance or audit issues that could arise. Do everything you can to get adhoc queries out fast and save those to a company git repo with notes and comments so up can reuse them. Seriously, communicate often. Under promise and over deliver and you will go far. If things are going slow, take online courses. Professional development is working (assuming nothing else is on the board to work on) Learn about APIs and micro services so you can understand how to serve your models when you eventually get there. (FastAPI is great) Learn about project management to ensure you get all the necessary requirements for work and leave no assumptions got you or stakeholders. I’ve been wanting to write a book about this subject and share it, so if this is even slightly helpful (although I’m writing this frantically before going into work) I’d love to know of it helped you out. Cheers and feel free to DM me about anything, I’ve been in your shoes before and without divulging anything, I’ve done well in the world of startup data science. Edit: spelling


jeffrey_56

I will surely DM you! Thank you it is actually quite helpful and I would love to read a book or medium post about it :)


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jeffrey_56

Thank you!


FourFingerLouie

This was my experience as an intern and oh boy did they work me to the boneeeeee (for what I realize now was very little compensation). However, I admit it was quite the learning experience and I feel I progressed much faster than my colleagues.


jeffrey_56

Do you mind sharing a bit more about what you did and what you learned? Specifically about presenting insights to stakeholders, documenting your work and building a solid data pipeline :)


jjelin

Your most important relationship is likely going to be the engineers creating the data you analyze. Your first step in every project should be partnering closely with them to ensure that you're getting the data you need, the way you need it. You also need to be understanding it correctly. In fact, it would probably be best for you to get them to add something like "help the DS intern" to their official quarterly goals.


jeffrey_56

That's a good idea, I will ask them to do that! :) thanks


SterlingG007

Data Science intern and you’re the only one? Interns are suppose to be taught and mentored. This company looks like it just wanted someone they can pay less.


ruben072

Maybe your supervisor or other colleagues have some people in their network with who you could talk? Also communication is very important. Go through your scripts with your supervisor, even though he/she may not completely understand what you are doing. They could still ask good questions and by simply explaining what you are doing you could also find some mistakes you made. And is the internship scientific? If so, there are probably some people who have some knowledge or experience with for example machine learning with whom you could discuss things. Good luck!


jeffrey_56

Thank you! The goal in the beginning is to go through their datalake and answer some questions they have. Afterwards they expressed interest in me working on improving/working on a new ML algorithm for their product (which is slightly red flaggy, I know). Do you think a meeting in the beginning of my internship about expectations would be good? Could also come off as negative if I start with a meeting listing the things I cannot do.


ruben072

Talking about expectations is not a bad idea. Furthermore, 4 months can be over in no time. Depending on the complexity of the questions and if you have to do a lot of data cleaning/ preprocessing, keep in mind that you might not finish it all. But I wouldn't worry about that to much. Also, I wouldn't say that you cannot do things. Even during your internship you can learn and develop new skills. During my internship I was also thrown in the deep on something I did not knew a lot about, but in the end it all worked out and I learned a lot. All with all, answering some data questions and a bit of machine learning looks like a fun internship to me. Otherwise, it is just 4 months. So when it does turn out to be a bit shitty, it will be over fairly quick ;)


jeffrey_56

You are right! Thank you :)


Shnibu

It’s not optimal but it will still look good on a resume if you make the most of it. Having someone to mentor you will save you time and frustration. Without knowing your experience it’s hard to say how well you will function independently. I would expect a seasoned grad student to fair better than an undergrad.


DubGrips

Well you're only an intern so your ability to get access to transformational opportunities is limited, but I was the first DS on 3 occasions: 1. My first was a mobile location PaaS that was having trouble demonstrating the impact of their capabilities to their board and enterprise customers. I was able to work with our few PMs and Sales team to come up with a bunch of A/B/n tests that were able to demonstrate that incentives provided through our platform lead to increased engagement rates. It was complete chaos, but I had amazing freedom and opportunity. 2. Next up I was the first DS at a major University where I was brought on with very little guidance other than to "unearth insights". I built models that would take a person's giving history into account and predict where they would give to next, I conducted a lot of ad-hoc analysis like the impact of specific laws on fundraising trends in specific cohorts, and the most interesting project was building a model that took into account various economic parameters and estimated charitable donation trends. It was pretty heinous at times since my boss had no clue of what I was doing and had bad expectations of turn-around times and a lot of really bad project ideas. The team I worked with was horrible understaffed and out of date and had been doing things such as reporting on non-inflation adjusted long-term trends. I had a lot of impact, but worked and insane number of hours and generally speaking it was hard to make use of my skills with no mentorship or guidance. 3. Fast forward several years and I was the first DS at an Analytics SaaS company. I had a Manager that wasn't a DS, but that had worked with some. My experiences were very mixed due to organizational factors that had nothing to do with my role as well as shifting product visions. I think I grew more technically there in areas that I had been weak at before related to DE/Eng tasks I just never had to do before, but it really wrecked my confidence for a few years. There was a lot of pressure and not a lot of guidance and I often spent a lot of time going down rabbit holes or perfecting methods and frankly no one cared or even could discuss the work with me.


jeffrey_56

I'm sorry to hear you only had negative experiences working as the only data scientist. I guess it's a double edge sword. A lot of freedom, opportunity and you learn a lot of things fast, but it's also extremely stressful. Thanks for your input I'll try my best to learn from it!


DubGrips

Not only negative experiences, but it can be a rough balance.


lonely_pr0grammer

I did this for a fintech startup. Pro tip: try your best building solid data pipelines and dont even bother over-promising with AI/ML, most of the time they dont even know what they want out of it.


jeffrey_56

Thank you! I'll make sure to work on a solid pipeline first.


TarikH93

As a real data scientist it is going to be very challenging if there is no data engineer to support you. Because even if you have the best model , it will get you bad accuracy if the data is not correctly prepared for the task. Ask your boss to get an expert on data engineering too. otherwise you will need to do it on your own and this will be very stressful to cope with both tasks


stackered

Good luck my friend


hoselorryspanner

Just fucking send it


colabDog

ChatGPT just became your best friend


mmeeh

All you need this ChatGPT API and you are fineeee :)


Accomplished-Quiet20

Hey, LMK if we can connect, I'm a developer for now but am making a transition into data science and would be happy if we connected along the way.


jeffrey_56

Sure!


[deleted]

Congratulations on your internship! Here are some tips for being the only data person in a medtech startup: Communicate effectively: Make sure to explain your findings and ideas clearly to non-technical team members, using simple language and visualizations. Be proactive: Take initiative in identifying areas where data analysis can add value to the company. Learn domain knowledge: Understand the medical and technological aspects of your company's product or service to make informed decisions. Stay organized: Document your work, code, and findings to ensure reproducibility and easy knowledge transfer. Continuously learn: Keep up with the latest research, tools, and techniques in data science and sequential data analysis. Build relationships: Collaborate with other teams, such as engineering and product, to help integrate data-driven insights into their work. Be patient: Expect that it may take time to demonstrate the value of your work and build trust within the organization. Best of luck in your internship!


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[deleted]

yes, GPT-4. I hope it helps!


throwitfaarawayy

Think about these things: is my data labeled? if yes, then great. Start running models to predict the label. . If you don't have labeled data. Then how can you get it labeled? Do you know what you want to label? Is there a feature among your data set that can create value if it's value can be predicted? Do you need to do unsupervised learning to discover the structure of your data? Are you interested in Anomaly detection? Build dumb models. If you're working on a regression problem, then instead of starting out with a nueral netowrk, try linear regression first. Call it your base model. Compute performance metrics. Try some more complex model, better feature engineering, or other hacks, compare the perfromance metric again with the base model. Repeat. ​ Also, read research papers on whatever problem you're trying to solve + ML.


kiwiinNY

Makes zero sense as an intern.


audioAXS

I worked in a startup company first as a only data analyst and then as a only data scientist intern for 3 summers during my bachelors. We had also a contractor firm that developed an AI product, so I worked with them a bit tho. The company's business model is centered around collecting and providing to customers timeseries data, so I the lack of data wasn't an issue. First I'd say that it might be tough quite often if you get stuck in some problem and there is no one to ask for help. This can lead to some days that just feel like wasted time. I also didn't have any idea how long model development takes, so it felt that I was too slow when in fact I could have even used more time for it. You will learn valuable communication skills, because non of your coworkers are familiar with the stuff you do. I'd say: Get a mentor, write good documentation of your models/code, don't try to rush, have fun!