What Is the Career Path for Data Scientists?

In this video, I talk about the career path for a data scientist across three horizons: a short term of 1-5 years, a medium term of 5-10 years, and a long term of 10+ years.

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[RichardOnData]

Fellow data scientists: what does your career path look like?

[tusharroy]

- Data science doesn't have a straightforward career path. It's a new field, starting in 2010, and is very broad and varies job-to-job and person-to-person. But data science should be a robust field going forward.

Short-term (1-5 years) = entry-level analyst / data scientist
- First role in DS, won't be exposed to whole DS pipeline until 1-2 years in
- See illustration of the AI heirarchy of needs - this illustrates the data science pipeline well.
- Early on, you'll likely focus on analytics and metrics, maybe some cleaning, AB testing, algos
- Later you might do more with AI/deep learning. If not, you may want to change companies in your first 5 years.
- You should also gain understanding of the data engineering and tasks involved earlier in the DS pipeline
- This broad exposure will give you an idea of what you may want to specialise in later
- A good DS study pathway is to learning SQL then R/Python very well. Then to go back later to learn Python/R well enough.
- As you solve problems, you'll compound your skills in the chosen language. Don't worry as much about knowing a tonne of languages straight away.
- At your current job, you should be able to branch into different technologies (javascript, julia etc) if you can find use-cases.
- Looking at new jobs, you may want to consider how it will let you expand your technical skillset.
- In 6-12 months, you'll get a good understanding of the domain you work in. But over 3-5 years, you'll learn an exceptional amount about your industry (healthcare, finance, automotive etc) and this will make you a much better data scientist and let you add strategic input in your job.
- When you start, you'll be a code monkey, solving problems given to you. But over time, you'll deal with unstructured problems or just situations where you need to find the right problem to solve, then figure out how to solve it and solve it.

Medium (5-10 years) = senior data science/data science manager
- By now you should have a good title and salary that reflects your ability and experience.
- This is also a good time to consider pivoting in your role. Maybe product manager, software engineer. Or stick to data science and become a subject matter expert (e.g. R shiny, NLP etc)
- You'll be managing initiatives/projects, managing people etc
- You won't be the head guy but you will be a thought-leader in your area of expertise

Long-term (10+ years) = looking towards Chief Data Scientist, CTO, CIO etc, even CEO
- Key IT areas: network architecture, big data engineering, information security management, security engineering, web software development. You'll dabble with these things
- 10 years is a very long time period to build experience in a particular career, so you'll have a lot of options

[eugenemensah]

I enjoy watching your videos. I'm an undergrad and I'm very interested in data science. You share some great insights and I always learn a lot thanks!

[jessespringer]

Thanks for sharing so many helpful thoughts

[mohammadbehdadjamshidi]

Richard, you are really amazing, what a beautiful and energetic description! As an Iranian researcher working in Czech Republic, I just say thanks for sharing your experience with the world. 😍🤗

[Santoshsusarla]

Your views and insights are simply awesome. Thanks!

[optimizacioneningenieria]

I'm studying a bachelor in biochemical engineering. I see that data science will have a great impact here. I agree with you about the importance of domain knowledge. Thanks for the video.

[DirrrtyD]

As someone studying data science, this helped validate my choice. Thanks for the video!

[fraser]

Wonderful insightful video, as always 👍🏽

[davideruggeri]

Great Richard, as always. Anyway I would like to get deeper about this topic, because a career last 40 years, and I guess it should be similar to the software engineer's one. Technical skills, in tech, dont last long and change so quickly, that it seems the only way to stay competitive is to go into management, CTO and then someone opens its own company. About the last one, how data science knoweldge/experience would be suitable to start a company? And so, which domain would be the best?

[haohuang]

Hi I wonder what industry are you working in? I'm now a marketing undergrads but trying to shift my career path by taking a data science master's degree. I hope to become a marketing scientist/analytics, but currently there's not too many info of this position/niche online. It would be great if you are familiar with it!

[vakilik]

Hey Richard I'm currently an undergrad student majoring in Information Science. I was wondering if I need to go back to school to get a Masters degree to advance my career. If so, what would be a nice masters degree to compliment my Information Science Degree. Thanks!

[jharnasjoerd]

Do data Science will be ending in late 2020s or 2030s???

[moviesscreen]

Funny: "Let's say you're five years in to data science." Smiles. "Hopefully your title kinda reflects that." Later on, "As well as a handful on generous pay raises!"
Question: Do you think the election was fraudulent, from a data perspective? Are you planning on doing any follow up on that?
Question: What do you think are the self-employment prospects for new and established data scientists?