This resource is intended for aspiring data scientists / data analysts looking to get started in the industry. It is an informal list of resources compiled based on feedback from data scientists at Facebook and the wider tech community. Thank you to Aaron Frazer for his time and investment in these resources!

Interview with a Data Scientist:

Can you please provide us with a brief description of your field?

I work as a data scientist/statistician at a large technology company.  I have advanced graduate degrees and do a combination of exploratory general research (i.e., publishing externally) and trying to solve specific internal company data analytics problems.  Data scientists vary in the type of work they do and in how directly applied the work is, which will depend on the size and nature of the company.  Data science in general involves using statistical algorithms to analyze and build models for data and make predictions, such as an algorithm for recommending future purchases based on past purchase history.

Do you know of any good LinkedIn resources? Facebook groups?

What is your current position and company?

Currently I am a research data scientist at IBM labs in Haifa.  I work on testing algorithms to improve our various analytics products and develop new ones.  IBM and other large companies of similar size, such as Intel and others typically offer more flexibility to work on research and projects that are more exploratory in nature.

How did you find your job? How do most people in your field find a job?

I happened to get in contact with my current supervisor (who was recruiting) through a several-steps-removed contact who had applied for the position and ended up getting another job.  In general, I received interviews at other companies by simply applying over LinkedIn or Glassdoor.  I’m not sure if this is the typical path.  I also networked by going to meetups and telling people I was looking for a position.

What experience do you need to get into your field?

One does not always need the most directly relevant work experience.  For instance, I applied at a few companies that focused on technology solutions, and I had never worked in this area.  The relevant experience will vary on the position.  I did have applied experience and understanding of various algorithms (and how to use them) and programming experience.  In these kinds of positions, you will undergo a technical interview where they will try to get a sense of your basic algorithm knowledge, ability to reason about a data analysis problem you are not familiar with, and understanding of coding concepts.  These are things you can learn or obtain through hands-on work, or through practicing specific skills.  One can get into the field if they have relevant experience (e.g. programming and some algorithms) and can demonstrate ability to learn quickly.

What degree should someone making Aliyah come with in order to break into your field /find a decent position in your field?

For data science, a BA or above in computer science, data science, statistics, or engineering (there is overlap in skills) is good.  There are a variety of bootcamps out there that attempt to teach people data science.  I do not have direct experience with these or know how successful they are in getting people jobs.  I think one would have to verify with the bootcamp and do some research on this, but it’s a skill one can gain some experience in with some very targeted training, which may be sufficient.  I am not sure how these certificates are regarded by recruiters, given that a cottage industry has evolved.  However, there is a strong demand for skilled people with the right skill set.

What experience do you need to get the position you have?

In addition to some theoretical understanding of algorithms, some hands-on programming experience, ideally in something like Python.  I think if one has programming experience in general, it can be transferred, but it is best if one can demonstrate past experience in Python or some of the common tools used.  For my particular position, one needs more advanced experience that shows one can think, research independently, and adapt techniques that they learned elsewhere to a given problem, but this is not always true for lower-level data science positions.

Does it make any difference whether one studied in Israel or abroad? What are the benefits?

I don’t think so.  The most important thing seems to be the ability to demonstrate in an interview the technical knowledge and thought process which they are seeking.  Our company is international, so many people come from Israeli universities (particularly Technion), but there are many Olim like myself who studied abroad.  English fluency (particularly technical) is an advantage.

What is the salary range?

It depends obviously on the person’s education and years of experience.  Also, a larger company will generally pay more than a startup.  I would say that the lower range is somewhere around 17,000 NIS bruto per month for someone earlier in their career, and up in 30-40,000+ NIS  bruto for people with particularly advanced experience.  It is quite wide.  Compared to other careers, there may be some more flexibility in negotiating or stating a desired salary.  If one is in a position to negotiate, one should do research into salary expectations.  They may even ask you about your salary expectations at an initial interview.  For instance, after my first successful interview, I stated a salary figure.  Later on, I realized I had undersold myself, but they were unwilling to raise their offer from that figure.  I ended up accepting my current position for other reasons.  The bottom line is that one should do some research as to what they can reasonably expect, and perhaps add 5 or 10 percent on top when asked what they expect.  This is common in this industry, not only in Israel.

Describe the personal growth opportunities that exist.

In data science and in related fields, one needs to be constantly up to date on developments in techniques and algorithms.  I am expected to take supplementary online education (e.g. Coursera) when relevant as part of my work, and to spend some of my time reading.  In general, pursuing additional online training is a good thing and is a major way of growing in the position.  The abilities for professional advancement in terms of promotions really depends on the structure of the particular company.  One can, for instance, become more of a manager, which means you direct a team of others and spend less hands-on time with analysis and more time directing larger goals.

Who are the major employers in your field?

IBM, Intel, Mobileye, Google, Facebook, Amazon, Microsoft, Rafael, CheckPoint, Waze, eBay, Elbit, Taboola, Riskified, PayPal.  Any large company, particularly a tech company, that relies on data analytics for its business, will employ a team of data scientists.  The size of the team that is dedicated to data efforts, as opposed to other aspects, will vary.  Also, data science positions can appear under several different names, such as “statistician”, “data scientist”, “data analyst”, etc.

What are the upcoming areas of specialty you would recommend?

Deep learning, neural networks, computer vision, robotic navigation, recommendation systems.

Major events/conferences in your field?

Israel Statistics Association, AI Data Science Summit.  There are also smaller meetup events.

How do you feel about working and living here in Israel?

I like it a lot. Fortunately, the salary in the tech field is very high compared to others in Israel.