Biologist. Wanting to transition to Data Science. How? How long will it take?

Data science is hard. You can do it but to become really proficient will take a lot of time. If you can find a suitable program, a MS in statistics would probably prepare you best. You can learn all the computer

science stuff on the job but you will never have the time to really dig deep into statistics outside of university.

This might help:

https://www.youtube.com/watch?v=jNeUBWrrRsQ&app=desktop

I work in the field you are looking to get into. I took the statistics route to get here. It really isn't all that thrilling and you will be surrounded by people who think they are the world's smartest person and their ideas are the one true path. Though it isn't all bad, it can be very stuffy. Think very hard about why you want to leave your current field and what you think data science will bring. A dull job isn't the worst thing that can happen.

I went through computer engineering/software engineering. You are probably a capable person, it'll take a year or so to get used to the basics, then a couple more years to have good feel for programming and some of the algorithms and a broader understanding, and maybe another year or two to get good at big data or other specific topics with data science. If you actually try I'd think you can be proficient in 3 or 4 years.

Upgrade wrote:

If I spent 20 hours/week for a year learning Python, R, SQL, statistics and math, and then went on to get a master's degree using these skills, would that be enough for an entry level position? What do you think?

Well, you've just essentially described a 30 credit bioinformatics program - why not just do that route?

what's your current salary and how much would you like to make?

You can learn SQL in like two weeks if you really wanted to.

Python and R will take several months (at least) to learn, depending on your existing skill set.

nagoya wrote:

what's your current salary and how much would you like to make?

You can learn SQL in like two weeks if you really wanted to.

Python and R will take several months (at least) to learn, depending on your existing skill set.

I currently make about $50,000/year in a pretty inexpensive part of the country. My rent is $300/month. I would like to make $70k+/year.

I know that it doesn't take that long to learn the basics, but I am wondering how long it would take to get into a real job, perhaps not necessarily a data scientist job, but maybe one as a data analyst (much easier from what I gather), and how long it would take to potentially get a job as a data scientist making $80k+ per year.

Do you want to stay in science? Probably some decent opportunities in life sciences with a little data science training.

Harambe wrote:

Do you want to stay in science? Probably some decent opportunities in life sciences with a little data science training.

Yeah I mean the OP would have a plausible story for wanting to get in to bioinformatics or computational genetics. I'm doing statistical genetics right now and it would be tough to get into it without a stronger background than the OP's, but plenty of people do come into it from other fields (I did, but my quantitative background was very strong). There are also data science positions at a lot of drug companies and so on.

If you sant to make more money do more interesting work and you have a biochem degree, you really should look into PA (physician assistant) school or med school. I’m a surgeon our PAs all make about $120,000 in an inexpensive part of the country. They are surgical PAs. You can choose you’re specialty. It’s only 2 years of school for you (maybe less with your current degree). So, more money and more interesting work. Hours are 40/week. Strictly. Those who work more make more and can earn 200k pretty straightforwardly.

Med school is a great route and your payoff will be higher, but a lot more schooling. 4 years MD or DO then residency. You get paid about 40-50k in residency. 3 year residencies (ER, Primary care, internal medivine) will earn $200,000 easily. 4year residencies like neurology or physical medicine, will earn 300-400 k. Surgeon are 5-7 year residencies and depending on specialty easily earn greater than 500k. Regularly 800-1million for some specialties.

PAs and doctors can work anywhere st anytime. I can quit and start fresh in any big or small city in the county at will. I never have to hope a position opens in a city. I can work on my own schedule.

Neurologists and PM&R rarely get paid that much...just saying. They are often paid less than PCPs unless they are doing a ton of procedures. ER salaries average 350K.

Residency usually pays 50-60k these days. Average loan burden for med school is around 200K these days.

I know a guy from med school who finished med school, but didn't like it and couldn't get into the residency he wanted.

Went to grad school and got experience and got a masters in a Data-science related field - took him about 3 years.

After that, got a data science job paying around 80-100k. he seems happy. Always posting on facebook about how awesome his life is, although some of this is a cope, he seems genuinely satisfied with his career.

I ended up doing the traditional med school/residency/fellowship route.. Now make about 400K a year but work much more than him.

Thanks for the input, but I have no desire to become an MD, DO, or PA. Also, just to be clear, I have a BS in biology and another BS in chemistry, not a single biochem degree.

David S wrote:

Harambe wrote:

Do you want to stay in science? Probably some decent opportunities in life sciences with a little data science training.

Yeah I mean the OP would have a plausible story for wanting to get in to bioinformatics or computational genetics. I'm doing statistical genetics right now and it would be tough to get into it without a stronger background than the OP's, but plenty of people do come into it from other fields (I did, but my quantitative background was very strong). There are also data science positions at a lot of drug companies and so on.

I have thought about Bioinformatics... Several years ago I worked in research in a lab at a university that did genetic stuff and really enjoyed it. As someone with only a BS I didn't get that deep into it though. What is your job like? How do you like it? I don't really want to work for a drug company...

You are a biologist, therefore

You are unable to understand statistical concepts.

You are poor at math, hence being terrified of logarithms and partial differential equations are something to do with cars.

You mention being good at excel... jesus wept.

You'll be no more than a glorified data clerk. Find some way to get at more "quantitative" things in your current field. Changing fields as suggested is unlikely to bring joy.

I am not a software developer wrote:

You can learn all the computer science stuff on the job but you will never have the time to really dig deep into statistics outside of university.

Amen, brother, Amen!

Your goal in graduate school isn't to learn everything you'll ever need to know to do your job. That'd be impossible. You want to come out of grad school with a mastery of the basic statistical tools, and the ability to pick up more advanced tools when needed. The hard part isn't the math. It's mostly just calculus and linear algebra (and maybe some measure theory and analysis). The hard part is cultivating your statistical maturity, so you know which tools work for which problems. Without that, you'll always be a little bit lost, never quite sure which tool to use or why.

An analogy to training routines might help. A coach can't just know the various building blocks that make up a training program, such as intervals, long runs, nutrition, weight training and so on. A coach also needs to know how these various training tools work together to support the goal of running faster. Otherwise, the coach won't be able to design a new program, or even tweak an existing program.

So yeah, the goal of grad school is to turn you from a runner into a coach. The problem is that you've been playing video games, so you don't know intervals from hill sprints.

Here's some practical advice for a simple first step that will tell you whether this plan is going to work. To get back up to speed on math, I'd start with linear algebra rather than calculus. It's key to any data science job, and there are lots of options for self-study. (Gilbert Strang, who's book I used to recommend to students who needed to bone up on linear algebra, has put lectures up on Youtube.)

If you can't do linear algebra, you should move on to Plan B.

Upgrade wrote:

I currently make about $50,000/year in a pretty inexpensive part of the country. My rent is $300/month. I would like to make $70k+/year.

I know that it doesn't take that long to learn the basics, but I am wondering how long it would take to get into a real job, perhaps not necessarily a data scientist job, but maybe one as a data analyst (much easier from what I gather), and how long it would take to potentially get a job as a data scientist making $80k+ per year.

You will most likely have to move to an expensive part of the country to get a job once you are qualified.

I transitioned from academia to data science and I went to a 3 month bootcamp. It was really helpful and I got s job shortly after. You do not need a master's. You'll pick up the stats that you need as you move on.

There are a lot of people spouting off about how much math you need and they're not right. Deep learning has advanced to the point that you can get by with a basic understanding of derivatives. Linear algebra is pretty helpful.

I agree with others that Python and SQL are essential. R is pretty easy to pick up once you've mastered those. Linked In has some decent free content for Python and I like Coursera/EdX/Udemy.

Good luck.