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Ask HN: Which new skills for a data science career?

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Re: Ask HN: Which new skills for a data science career?

#31

Post by gompertz »

edot wrote: post #19
jstx1 wrote: post #2

Do you have a PhD? If you do, it's going to help a lot with the transition. Skills for someone like you to work on - Python, the Python data ecosystem, machine learning, deep learning, being a good software developer. Things not to worry about right now - Kubernetes, DevOps, cloud providers. You don't need JavaScript. Don't learn any Tableau/PowerBI and don't apply for jobs that require them unless you want a more an…

Seconding this. Take Tableau off of your resume unless you want to be a dashboard monkey (sorry, “BI Developer”). Dashboards != analytics, but lots of companies seem to think they do. I would suggest looking at the Certified Analytics Professional certification from INFORMS. Operations Research is the original data science, and preparing for and passing the test is a good signal that you understand analytics. Machine…

Sigh..another program that requires you to maintain your certificate by doing PDUs. This is like a 90s dark pattern that still creeps up from time to time. I can't get behind any organization that threatens to take education away from you.

Re: Ask HN: Which new skills for a data science career?

#32

Post by rafiki6 »

The reason the skills matrix seems overwhelming is because there is no true singular "data scientist" role. It's a title that's been abused. So my answer is, it depends a lot on the TYPE of data scientist you want to become:

- Data Scientist MIGHT mean Applied ML Scientist (important distinction) - Data Scientist MIGHT mean Data Engineer - Data Scientist MIGHT mean ML Engineer - Data Scientist MIGHT mean Data Analyst - Data Scientist MIGHT mean Statistician - Data Scientist MIGHT mean Product Analyst

The traditional idea of a data scientist for the last decade or so is someone who is able to do insight extraction, create models (ML and otherwise) and build dashboard and presentations. In practice this has mostly proved to not be practical and little value is being extracted from the role, so a mature organization will properly break out the responsibilities into the above mentioned functional areas.

I think it's super important that you reach out to industry data scientists at companies or in domains you're interested in and ask them what it is that they actually do on the daily. Be careful with most data science roles as they are really just data analyst roles in disguise.

Very few true data "science" roles exist, and I'd argue that might you not actually want to work in those roles since they likely exist in companies that have no idea what they want out of them.

That being said I think the 2 absolutely crucial technical skills to have for almost any modern data related job will be:

- Python + Pandas - SQL

That's really going to be the technical foundation to make a data career in industry.

The breadth of other skills and required knowledge is too much for any single person or post to tell you.

I'm not entirely sure what your PhD is in, but if it has an associated domain in industry and if you're actually interested in that domain, I would recommend starting there and seeing what Data Scientists with similar academic backgrounds as you might be doing. LinkedIn is a great place to find people and connect!

Best of luck.

Re: Ask HN: Which new skills for a data science career?

#33

Post by logosmonkey »

Truthfully, most roles advertised as data science in most corporations and Healthcare orgs are mostly just data wrangling for presentations or dashboard work. You have plenty of skillset to get in the door at most places if you interview well. Your big problem will be weeding through the jobs to find one where you will really get to do data science working and not just write somewhat complex sql queries for people.

Re: Ask HN: Which new skills for a data science career?

#34

Post by kj4211cash »

I made this transition a few years ago. Prioritize studying Python. Leetcode. Make sure you're familiar with git. And then pick 2 or 3 sub-genres of Data Science and study those. Operations Research, experimentation and statistical tests, Causal Inference, Computer Vision, NLP, etc. Then apply for Senior Data Scientist or Senior Applied Scientist roles in those areas. The hiring process is broken and based on quickfire technical tests. There are huge numbers of people trying to break in to DS. Be prepared for lots of rejections. Be positive during initial calls with recruiters; they are just looking for a reason to filter you out and don't actually know much about the job. Good luck!

Re: Ask HN: Which new skills for a data science career?

#35

Post by f00b4r_ »

trevormcneal wrote: post #17
jstx1 wrote: post #2

Do you have a PhD? If you do, it's going to help a lot with the transition. Skills for someone like you to work on - Python, the Python data ecosystem, machine learning, deep learning, being a good software developer. Things not to worry about right now - Kubernetes, DevOps, cloud providers. You don't need JavaScript. Don't learn any Tableau/PowerBI and don't apply for jobs that require them unless you want a more an…

Came here just to weight in for each and every point. This is the best answer so far. PhD is seem as a magical badge of super power, even if you can get a job without one, consider having it, is a 1.5x-2x salary multiplier.

I've only seen PhD's increase salary for machine learning researcher positions. For ML eng, ML ops, and analytics, I haven't seen any pay differential. YMMV

Re: Ask HN: Which new skills for a data science career?

#36

Post by [deleted] »

f00b4r_ wrote: post #35
trevormcneal wrote: post #17

Earlier quoted context omitted.

Came here just to weight in for each and every point. This is the best answer so far. PhD is seem as a magical badge of super power, even if you can get a job without one, consider having it, is a 1.5x-2x salary multiplier.

I've only seen PhD's increase salary for machine learning researcher positions. For ML eng, ML ops, and analytics, I haven't seen any pay differential. YMMV

[deleted]

Re: Ask HN: Which new skills for a data science career?

#37

Post by xLaszlo »

- Find out what you want to do

  - Think about what are your strongest applicable skills

  - Talk to as many DSes/MLEs/MLOps engineers you can

  - Experiment with various fields (watch videos, OSS work etc)
- Find comapnies that you actually want to work for

- Find out what DS means at those places and what do they do and if that's what you want to do. Ask as many questions about the details of the job as possible at the interview, the hiring manager will be glad you want to avoid getting a job you are not committed.

Essentially: Do your homework then make a decision that is good for _you_ rather than trying to fit to an abstract idea.

Re: Ask HN: Which new skills for a data science career?

#38

Post by akhmatova »

edot wrote: post #19
jstx1 wrote: post #2

Do you have a PhD? If you do, it's going to help a lot with the transition. Skills for someone like you to work on - Python, the Python data ecosystem, machine learning, deep learning, being a good software developer. Things not to worry about right now - Kubernetes, DevOps, cloud providers. You don't need JavaScript. Don't learn any Tableau/PowerBI and don't apply for jobs that require them unless you want a more an…

Seconding this. Take Tableau off of your resume unless you want to be a dashboard monkey (sorry, “BI Developer”). Dashboards != analytics, but lots of companies seem to think they do. I would suggest looking at the Certified Analytics Professional certification from INFORMS. Operations Research is the original data science, and preparing for and passing the test is a good signal that you understand analytics. Machine…

Take Tableau off of your resume unless you want to be a dashboard monkey (sorry, “BI Developer”).

As opposed to a regression-and-printf monkey (sorry, "Data Scientist")?

Like it or not - a lot of companies run on dashboards. To, you know, actually get their data out to people. So they can run their business, so you can get paid.

If you dig math and like doing mathy things, good for you. There's no need to be snide about the work that others do that (like it or not) as just as essential to keeping the business afloat as yours.

You are absolutely right though that pigeonholing in this industry is very much a thing. And intellectual honesty, not so much. Lesson being -- if one is targeting certain fields, it is often best to leave certain things off our resumes (or tone them way down).

Re: Ask HN: Which new skills for a data science career?

#39

Post by rbartelme »

I recently made the transition from academia to industry (also a PhD holder). I would echo a lot of what other commenters said about learning python and the associated data science tooling. Coming from an R heavy scientific discipline (quantitative ecology), I found python to be quite a bit better at things that base R struggled with, particularly string manipulations.

Aside from programmatic and cloud tools as identified in your post, one of the biggest hurdles is whittling down your academic CV into a resume. Spending time re-framing your academic accomplishments in the short form will be the best time investment for getting in for interviews. I ended up following the google XYZ resume formula: https://www.inc.com/bill-murphy-jr/google-recruiters-say-the... It kind of hurts to distill your academic achievements into "Published [X] peer reviewed papers [Y] by driving the analysis [Z]", but I think it really helped me start getting calls vs. desk rejects. Relatedly, only include publications that either highlight your expertise for a specific job posting or if they further highlight your expertise in statistics in a way that could set you apart from other candidates.

Re: Ask HN: Which new skills for a data science career?

#40

Post by mateo411 »

chaps wrote: post #24

Since you already know R/STATA/Linux/SQL, you're already way ahead of most people. You'll find that a lot of the specific technical stuff is project/industry dependent and since you're just starting in the field, think of any hard requirements for a specific technology as a warning sign. Good employers will give you room to learn their niche technicals. The thing about data sciencey stuff is that the data you're work…

So, basically data engineering. If you want to be good at data science you should at least be a mediocre data engineer.
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