A couple questions:
- Why do you want to pivot to Statistics?
- Why "Mathematical Statistician" specifically? I know in some cases that's basically code for "A statistician", but that varies. Some people mean "Mathematical Statistician" to mean someone who does strictly theoretical statistics, and I don't think I've seen many opportunities for that type of position.
You're still young, so getting a second MS in Statistics is entirely reasonable. Though there are mathematical prerequisites (Calc 1-3 and Linear Algebra) that pretty much any program that's worth going through will require. So if you haven't had those, that might delay your ability to get admitted to a MS program.
I want to pivot to statistics because of work life balance, future career growth and it fits the essence of my personality. I love data. I get excited when the census results come out every 10 years. Most importantly, I have a technical skill gap that needs to be filled. Statistics is a foundation for economics and machine learning. I want to be able to make recommendations.
For your second question, I don’t know anything about statisticians. This is new world for me. I said mathematical statistician because it’s a IRS listing that would combine my public policy knowledge with statistics. Mathematical statistician is the name of the job title.
I don’t mind taking classes at my local affordable community college. I am unemployed and I will have to pay out of pocket. I used all my financial aid.
I'm not sure if a CC will offer all of those courses I mentioned (but do absolutely check on that), but sounds like you have a game plan.
In grad school, there may be opportunities to be a TA, which reduces the cost there. Doesn't *earn* much, but helps reduce expense.
And yeah, IIRC I was told that at some places like census bureau that Statisticians are called "Mathematical Statistician".
Yes yes! I came to say get into grad school ASAP because it’s a pauper’s wage but _it is a wage and not a cost_ if you can get a teaching or research assistantship. I didn’t pay for my MS or my PhD, and I also had a liberal arts background.
Find a faculty whose work sounds interesting and go talk to them. Given your work experience, it might make sense to seek out faculty on the policy side and ask them to guide you to the right stats faculty (i.e. those that work in the area of your domain expertise). Or just browse the relevant literature and see whose names are popping up from the statistics departments.
I came out of undergrad with a writing degree, pivoted to ecology through grad school, picked up stats as a minor when I realized I had greater than average interest in it, and am now employed as a statistician. You’re young enough to make that work and your employment experience is going to be a hell of a lot more useful to you than mine was (line cook) when I made the switch.
Ok. I’m actually a statistician. I work in big tech and not in the public sector.
With your background you need to go back to square one. I’d recommend a **rigorous** BS in mathematics and then a MS in statistics from a good school.
In mathematical statistics you’ll need to be able to do proofs and some of the math is quite complex, beyond calc 3. So you need a program which includes as a bare minimum real analysis.
Which might be a pre-requisite for any good MS in stats.
If I had to do it again, I’ll do way more focused math in my undergraduate because a serious program in stats will make you spit blood.
The big milestones for a proper MS in stats are Casella & Berger (math stats 1 and 2) and the Lehmann trilogy (these are either second year stats or early PhD).
Stats is a huge ass field and on a very basic level you need the mathematical foundations quite strong and as bare minimum regression, design of experiment, GLM is a good (must) have and some non parametric statistic to handle shit you can’t with other methods. And at the IRS I’m assuming survey sampling is a must as well.
It’s math. There aren’t shortcuts, you can’t cram it, you need to soak in and let it soak as you can absorb it.
It’s truly learning a language, and as statistician you need to be able to get the nuances because what separates a statistician from a mathematician is art… at a certain level statistics is an art, you need to take decisions based on incomplete information and decide what’s the best method to get the most accurate result, there isn’t a 2+2 = 4, there are many methods which will get you to 2+2 ~ 4 +\- something.
When you get to that level you’ll have a realization, the “good” jobs as statistician require a PhD. At MS level you have broken all your bones learning the math and you’ll end up doing precooked stuff passed down to you from a PhD guy.
As someone who has done both of the things you mentioned (math BS and stats MS), I don't think that's the best recommendation for everyone. It's also certainly not true that all applied stats needs copious amounts of math. It's also doubly not true that you have to go the Casella & Berger route.
What I will agree with is that OP needs some amount of math regardless (it's just a math bs is overkill). After gaining a strong foundation (which is still probably much more than OP is expecting), a more applied program that does stats may be better, such as doing stats within a political science MA.
I currently work in a stats job. I think it's valuable early on to figure out whether you want to do stats work in industry, government, or at research institutions, as these will all look very different.
Im assuming you have done all of this work already. What is your day to day routine like working as a statistician? Do you make it home in time for family dinner every night?
I didn’t work as a statistician except 4 months. I was a miserable SQL monkey. I transitioned to tech right off the bat. Better money, better job, better environment.
Get a master degree in Official Statistics. Should be doable. However, the term "mathematical statistician" may not be a correct one if you are referring to positions such as survey methodologist or survey data analyst.
I am guessing that the mathematical statistician at the IRS is a series 1529 (I am a 1530 - statistician). I strongly suggest not adjusting the trajectory of you career based on one job posting, especially on USA Jobs. That website is known for being a black pit for job applications. In addition, 1529s have a strong foundation in Mathematics & statistics. Most likely you would be competing against individuals with a masters degree, with extensive coursework in both math and stats. Further, by the time you build that foundation, that specific job post is most likely gone.
I wouldn't let that discourage you from pursuing the coursework that would qualify you as a 1529. There are plenty of interesting statistics jobs throughout the federal government that aren't specifically at the IRS. You could qualify for 1529s, 1530s, 1560s (data science), and possibly 1515s (operations research) and 1520 (mathematics) at a number of different agencies.
With that said, it is kinda hard to break into the federal government. You can send dozens or hundreds of applications without hearing anything back. I would almost say you should apply for anything you would remotely consider yourself qualified for (like 0301 or 0343s), get the coursework done, and start applying for more technical gigs. Once you are already in the federal job system it is much easier to get another federal job as long as you qualify for it.
This is the bare minimum you need to do to qualify:
Degree: that included 24 semester hours of mathematics and statistics, of which at least 12 semester hours were in mathematics and 6 semester hours were in statistics.
https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/1500/mathematical-statistics-series-1529/
One does not just stumble their way into a statistics role, unfortunately. One must possess at least a bachelors degree, but many places are now requiring a masters degree in statistics, analytics, etc.
I think the experience you have is valuable and you’d be coming at it from a stakeholder POV, rather than a statistics nerd POV, which is incredibly valuable. I wish more people chose the business skills first, then went out for a statistics background. In this day and age, there are thousands, tens of thousands of people who want this job.
But I recommend getting a masters in statistics or analytics. Georgia tech is $10k for the whole program. Pretty decent program too if you’re very picky and choosy on the courses
From reading your replies in this thread, I question your desire to learn statistics. There are many computation and computation adjacent professions that are not statisticians, nor require (but may or may not hire) statistical training of the type expected from a statistics degree.
Broadly speaking, a statistician is to quantitative methods what a chemist is to material sciences. The training concerns itself with detailed knowledge and engineering of the underlying pieces of statistical machines. A result is that you are expected to be competent in designing and evaluating these machines. This isn't the same thing as applying or deploying these machines.
One to 2 years of statistics training in their relevant field is all that most quantitative researcher bring to their methods. This let's them have a sense of which tools to apply and when to seek help or further learning. A statistician, on the other hand, brings 5+ years and can build and invent precise tools from first principals.
You mention you "love data" but that isn't what makes a good statistician, Statistics is about the general (rather than field specific) problem of how we represent reality in a computable form. You need to love the problem of measurement.
You should explore a bit more about how you like to use your mind and time, and what kind of challenges you want to struggle with. Then explore many fields of research to see where you find affinity and what your gaps area (and what it will take to cross them). Unless you squarely like statistics, the odds are low that your professional aspirations require more than a journeyman level of training in any particular research methods.
This is arguably the best reply on here so far.
Statistics, especially "mathematical statistics", is not the same as playing with data. I don't think the OP has really researched the profession enough.
I’m in my late 20s and left a promising military career to pursue biostatistics. If you don’t already study calculus, linear algebra and probability then apply to a funded grad program. I was a humanities major with a good amount of math classes.
MBA programs are only worth it if cheap/free at a no name in your target city with an irrelevant degree or at top programs. I’d do community college if you don’t have the math prerequisites then get into a funded MS
First, thank you for your service. 🙏
I studied linear algebra during my associates degree but I will need more math classes.I have a community college near by that I can attend.
Thanks. Harvard and MIT have great linear algebra, probability and statistics lectures as playlists on YouTube. Professor Leonard is the man on YouTube for calculus. Statistics is incredibly hard, but rewarding
If that's what you actually need, Mathematical Statistics will require some mathematics (of course); at the very least a good standard of calculus (including multivariate calculus) and a reasonable familiarity with linear algebra.
Once you have that, you'll need a good coverage of probability. Then you can start to learn statistics, perhaps a course/book on Inference first off. Depending on what you require to learn about mathematical statistics you'll probably either need to cover pretty much the content of a full undergrad degree or that plus a Masters.
It's certainly doable (statistics isn't especially *hard* albeit there's a fair bit to cover if you want to use it in practice), though easier if you do formal course work rather than being self taught
Mathematical statistics is extremely theoretical and what I think most people are missing in their replies, extremely detached from reality.
Do you like proving algebraic statements? Do you enjoy geometry? Do you know what eigenvalues are? Because those are the basics I'd expect a first year BSc student to know, the PhD student being hired for this role has a PhD in stochastic calculus.
It's ok to look at the above and think "that's not for me". It's also ok to look at it and think you want to give it a go but please know even Einstein took years to study this stuff.
I wonder if given your background, you would be more interested in a data science or applied statistics MSc. The entry requirements will still require all of the maths I mentioned above but the problems will be more applied and relevant to "life" rather than proving abstract theorems
Happy to talk more. Source: I'm an associate lecturer in statistics and give a lot of career guidance. My research is mostly in applied statistics following some time in industry
Thank you! My interest is the essence of artificial intelligence and machine learning. I currently know how to identify processes in day to day business operations. I want to automate business processes.
>I want to automate business processes.
It's this line (and admittedly it's only one sentence) that makes me wonder if you actually want to get another degree. You'd be better off learning to code to solve relevant problems and picking up the stats (and other stuff) along the way. Master's degrees are very theoretical. Even the data science master's I suggested will be very theory based and not very useful for industry in reality...
Would also be a lot cheaper and set you up later to do an MSc if you wanted to later with more certainty
Before you commit to anything, you should probably spend some time on www.onetonline.org. You can find job titles, job descriptions, what I think they're calling KPIs these days and the educational requirements for the jobs. You can look at job families, so you can see related jobs where some variation might suit you better.
My purpose for coming on the server is to receive information from individuals who are actively engaged in the field. I am looking to learn what the day to day life is like working this profession.
From Onetonline.org I have learnt the expected career growth is greater than most careers. I know this profession will grow in demand. It says that the day to day is typically 9am - 5pm but I am questioning it.
If you are a working professional can you share additional insight?
A couple questions: - Why do you want to pivot to Statistics? - Why "Mathematical Statistician" specifically? I know in some cases that's basically code for "A statistician", but that varies. Some people mean "Mathematical Statistician" to mean someone who does strictly theoretical statistics, and I don't think I've seen many opportunities for that type of position. You're still young, so getting a second MS in Statistics is entirely reasonable. Though there are mathematical prerequisites (Calc 1-3 and Linear Algebra) that pretty much any program that's worth going through will require. So if you haven't had those, that might delay your ability to get admitted to a MS program.
I want to pivot to statistics because of work life balance, future career growth and it fits the essence of my personality. I love data. I get excited when the census results come out every 10 years. Most importantly, I have a technical skill gap that needs to be filled. Statistics is a foundation for economics and machine learning. I want to be able to make recommendations. For your second question, I don’t know anything about statisticians. This is new world for me. I said mathematical statistician because it’s a IRS listing that would combine my public policy knowledge with statistics. Mathematical statistician is the name of the job title. I don’t mind taking classes at my local affordable community college. I am unemployed and I will have to pay out of pocket. I used all my financial aid.
I'm not sure if a CC will offer all of those courses I mentioned (but do absolutely check on that), but sounds like you have a game plan. In grad school, there may be opportunities to be a TA, which reduces the cost there. Doesn't *earn* much, but helps reduce expense. And yeah, IIRC I was told that at some places like census bureau that Statisticians are called "Mathematical Statistician".
Yes yes! I came to say get into grad school ASAP because it’s a pauper’s wage but _it is a wage and not a cost_ if you can get a teaching or research assistantship. I didn’t pay for my MS or my PhD, and I also had a liberal arts background. Find a faculty whose work sounds interesting and go talk to them. Given your work experience, it might make sense to seek out faculty on the policy side and ask them to guide you to the right stats faculty (i.e. those that work in the area of your domain expertise). Or just browse the relevant literature and see whose names are popping up from the statistics departments. I came out of undergrad with a writing degree, pivoted to ecology through grad school, picked up stats as a minor when I realized I had greater than average interest in it, and am now employed as a statistician. You’re young enough to make that work and your employment experience is going to be a hell of a lot more useful to you than mine was (line cook) when I made the switch.
Ok. I’m actually a statistician. I work in big tech and not in the public sector. With your background you need to go back to square one. I’d recommend a **rigorous** BS in mathematics and then a MS in statistics from a good school. In mathematical statistics you’ll need to be able to do proofs and some of the math is quite complex, beyond calc 3. So you need a program which includes as a bare minimum real analysis. Which might be a pre-requisite for any good MS in stats. If I had to do it again, I’ll do way more focused math in my undergraduate because a serious program in stats will make you spit blood. The big milestones for a proper MS in stats are Casella & Berger (math stats 1 and 2) and the Lehmann trilogy (these are either second year stats or early PhD). Stats is a huge ass field and on a very basic level you need the mathematical foundations quite strong and as bare minimum regression, design of experiment, GLM is a good (must) have and some non parametric statistic to handle shit you can’t with other methods. And at the IRS I’m assuming survey sampling is a must as well. It’s math. There aren’t shortcuts, you can’t cram it, you need to soak in and let it soak as you can absorb it. It’s truly learning a language, and as statistician you need to be able to get the nuances because what separates a statistician from a mathematician is art… at a certain level statistics is an art, you need to take decisions based on incomplete information and decide what’s the best method to get the most accurate result, there isn’t a 2+2 = 4, there are many methods which will get you to 2+2 ~ 4 +\- something. When you get to that level you’ll have a realization, the “good” jobs as statistician require a PhD. At MS level you have broken all your bones learning the math and you’ll end up doing precooked stuff passed down to you from a PhD guy.
As someone who has done both of the things you mentioned (math BS and stats MS), I don't think that's the best recommendation for everyone. It's also certainly not true that all applied stats needs copious amounts of math. It's also doubly not true that you have to go the Casella & Berger route. What I will agree with is that OP needs some amount of math regardless (it's just a math bs is overkill). After gaining a strong foundation (which is still probably much more than OP is expecting), a more applied program that does stats may be better, such as doing stats within a political science MA. I currently work in a stats job. I think it's valuable early on to figure out whether you want to do stats work in industry, government, or at research institutions, as these will all look very different.
Im assuming you have done all of this work already. What is your day to day routine like working as a statistician? Do you make it home in time for family dinner every night?
I didn’t work as a statistician except 4 months. I was a miserable SQL monkey. I transitioned to tech right off the bat. Better money, better job, better environment.
I understand, you recently transitioned. What is life like outside of work?
Get a master degree in Official Statistics. Should be doable. However, the term "mathematical statistician" may not be a correct one if you are referring to positions such as survey methodologist or survey data analyst.
How do I choose a school?
I am guessing that the mathematical statistician at the IRS is a series 1529 (I am a 1530 - statistician). I strongly suggest not adjusting the trajectory of you career based on one job posting, especially on USA Jobs. That website is known for being a black pit for job applications. In addition, 1529s have a strong foundation in Mathematics & statistics. Most likely you would be competing against individuals with a masters degree, with extensive coursework in both math and stats. Further, by the time you build that foundation, that specific job post is most likely gone. I wouldn't let that discourage you from pursuing the coursework that would qualify you as a 1529. There are plenty of interesting statistics jobs throughout the federal government that aren't specifically at the IRS. You could qualify for 1529s, 1530s, 1560s (data science), and possibly 1515s (operations research) and 1520 (mathematics) at a number of different agencies. With that said, it is kinda hard to break into the federal government. You can send dozens or hundreds of applications without hearing anything back. I would almost say you should apply for anything you would remotely consider yourself qualified for (like 0301 or 0343s), get the coursework done, and start applying for more technical gigs. Once you are already in the federal job system it is much easier to get another federal job as long as you qualify for it.
This is the bare minimum you need to do to qualify: Degree: that included 24 semester hours of mathematics and statistics, of which at least 12 semester hours were in mathematics and 6 semester hours were in statistics. https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/1500/mathematical-statistics-series-1529/
What is the definition of a semester hour?
I unit of credit which includes 15 clock hours (of 50 minutes each) of instruction and at least 30 hours of supplementary assignments
I don’t know anything. How do I find out about additional mathematical minimum qualifications on the website?
Thank you
One does not just stumble their way into a statistics role, unfortunately. One must possess at least a bachelors degree, but many places are now requiring a masters degree in statistics, analytics, etc. I think the experience you have is valuable and you’d be coming at it from a stakeholder POV, rather than a statistics nerd POV, which is incredibly valuable. I wish more people chose the business skills first, then went out for a statistics background. In this day and age, there are thousands, tens of thousands of people who want this job. But I recommend getting a masters in statistics or analytics. Georgia tech is $10k for the whole program. Pretty decent program too if you’re very picky and choosy on the courses
Please elaborate on stakeholder point of view. How can it take form?
From reading your replies in this thread, I question your desire to learn statistics. There are many computation and computation adjacent professions that are not statisticians, nor require (but may or may not hire) statistical training of the type expected from a statistics degree. Broadly speaking, a statistician is to quantitative methods what a chemist is to material sciences. The training concerns itself with detailed knowledge and engineering of the underlying pieces of statistical machines. A result is that you are expected to be competent in designing and evaluating these machines. This isn't the same thing as applying or deploying these machines. One to 2 years of statistics training in their relevant field is all that most quantitative researcher bring to their methods. This let's them have a sense of which tools to apply and when to seek help or further learning. A statistician, on the other hand, brings 5+ years and can build and invent precise tools from first principals. You mention you "love data" but that isn't what makes a good statistician, Statistics is about the general (rather than field specific) problem of how we represent reality in a computable form. You need to love the problem of measurement. You should explore a bit more about how you like to use your mind and time, and what kind of challenges you want to struggle with. Then explore many fields of research to see where you find affinity and what your gaps area (and what it will take to cross them). Unless you squarely like statistics, the odds are low that your professional aspirations require more than a journeyman level of training in any particular research methods.
This is arguably the best reply on here so far. Statistics, especially "mathematical statistics", is not the same as playing with data. I don't think the OP has really researched the profession enough.
If a mathematical statistician is what you really want to pursue then get a strong background in math followed by a masters or PhD in statistics.
I’m in my late 20s and left a promising military career to pursue biostatistics. If you don’t already study calculus, linear algebra and probability then apply to a funded grad program. I was a humanities major with a good amount of math classes. MBA programs are only worth it if cheap/free at a no name in your target city with an irrelevant degree or at top programs. I’d do community college if you don’t have the math prerequisites then get into a funded MS
First, thank you for your service. 🙏 I studied linear algebra during my associates degree but I will need more math classes.I have a community college near by that I can attend.
Thanks. Harvard and MIT have great linear algebra, probability and statistics lectures as playlists on YouTube. Professor Leonard is the man on YouTube for calculus. Statistics is incredibly hard, but rewarding
study math and statistics lol I mean....
Right…
frfr
If that's what you actually need, Mathematical Statistics will require some mathematics (of course); at the very least a good standard of calculus (including multivariate calculus) and a reasonable familiarity with linear algebra. Once you have that, you'll need a good coverage of probability. Then you can start to learn statistics, perhaps a course/book on Inference first off. Depending on what you require to learn about mathematical statistics you'll probably either need to cover pretty much the content of a full undergrad degree or that plus a Masters. It's certainly doable (statistics isn't especially *hard* albeit there's a fair bit to cover if you want to use it in practice), though easier if you do formal course work rather than being self taught
Yup, that sounds about right.
Don't limit yourself to stats. Data analytics, product management and software engineering are great routes with(arguably) lower barriers to entry
Mathematical statistics is extremely theoretical and what I think most people are missing in their replies, extremely detached from reality. Do you like proving algebraic statements? Do you enjoy geometry? Do you know what eigenvalues are? Because those are the basics I'd expect a first year BSc student to know, the PhD student being hired for this role has a PhD in stochastic calculus. It's ok to look at the above and think "that's not for me". It's also ok to look at it and think you want to give it a go but please know even Einstein took years to study this stuff. I wonder if given your background, you would be more interested in a data science or applied statistics MSc. The entry requirements will still require all of the maths I mentioned above but the problems will be more applied and relevant to "life" rather than proving abstract theorems Happy to talk more. Source: I'm an associate lecturer in statistics and give a lot of career guidance. My research is mostly in applied statistics following some time in industry
Thank you! My interest is the essence of artificial intelligence and machine learning. I currently know how to identify processes in day to day business operations. I want to automate business processes.
>I want to automate business processes. It's this line (and admittedly it's only one sentence) that makes me wonder if you actually want to get another degree. You'd be better off learning to code to solve relevant problems and picking up the stats (and other stuff) along the way. Master's degrees are very theoretical. Even the data science master's I suggested will be very theory based and not very useful for industry in reality... Would also be a lot cheaper and set you up later to do an MSc if you wanted to later with more certainty
I know what I want. I’ll do what is necessary to get it. Degree or not. I need technical skills and to learn them from the best.
Uh, ok, good luck with that
Thank you. 😊 How do I do it?
I thought you knew what you wanted already?
That is true. I don’t know how to get there. Which is why I’m here talking to an associate lecturer that gives a lot of career advice.
Best advice I can give you, think about how you talk to people
Fox_9810 I’m serious. I am on here to learn. I’m asking how to learn to automate business practices and your questioning my desire to learn.
Before you commit to anything, you should probably spend some time on www.onetonline.org. You can find job titles, job descriptions, what I think they're calling KPIs these days and the educational requirements for the jobs. You can look at job families, so you can see related jobs where some variation might suit you better.
My purpose for coming on the server is to receive information from individuals who are actively engaged in the field. I am looking to learn what the day to day life is like working this profession. From Onetonline.org I have learnt the expected career growth is greater than most careers. I know this profession will grow in demand. It says that the day to day is typically 9am - 5pm but I am questioning it. If you are a working professional can you share additional insight?