Getting into Data Science FAQs

Getting into Data Science FAQs

Advertising Advertising

I often see similar questions in my inbox or asked in webinars. I’d like to set the record straight with data. However, I didn’t need to start from scratch, there was an excellent article on KD Nuggets by Jeff Hale. Here is the link to his article: “The Most in Demand Skills for Data Scientists”. He had already scoured multiple job search site and aggregated data on the demand for different skills for data scientist. I recreated some of his analysis myself, so that I could come up with some points for this article, and to make sure his numbers matched mine before posting. The charts I created below are based on data from searches on indeed.com only.

A search for “Data Scientist” was the denominator, and the numerator would be “Data Scientist” plus another term I was looking to see results for. I’m not sure how many job descriptions listed on indeed.com might be duplicates, so this is not gospel, but still interesting.

This article will cover a couple of “Frequently Asked Questions” using the methodology above (that was adopted from Jeff).

Questions I’m frequently asked:

  • Should I learn R or Python?
  • As a Computer Science major, can I get into data science?
  • How important is SQL?

Should I learn R or Python?

This would most likely be the most frequently asked question (although I’ve never analyzed the questions that I’m asked).  In Jeff’s article, you were able to see that Python has the edge in terms of coming up in job listings. I recreated the methodology for myself to look at this a little further.

55% of the job listings actually list both tools, as in the company would like to see that you have experience with “Python and/or R”.  That should make those who have a preference for one tool feel better.  If you’re looking to pick up either R or Python and you’re just getting your hands dirty, I’d suggest Python.  For listings that only specify one tool, Python is almost 5x more likely to be listed as the tool of choice compared to R.

I was happy to see this, as I’ve mentioned in a number of webinars and comments on social media that it “feels like” Python is slightly more popular.  It would have been a bummer if I had been giving misinformation this whole time.

% of Data Science Positions Mentioning a Particular Skill on Indeed.com


Pulled this data by doing a search on indeed.com 11/2018

As a Computer Science major, can I get into data science?

I’m always surprised when I see this question, because as someone who’s been in the field for a long time, it just seems clear that this is a fantastic skill as your foundation for moving into data science.  Data science requires a number of different skills to be successful, and being able to program is definitely one of the core pillars.  Analytics and Statistics are coming in first, but Analytics and Statistics could easily be mentioned somewhere in the job description other than specifically where preferred degrees are mentioned.  If a job description says “computer science” they’re most likely speaking to the degrees they would prefer from candidates.  More than 50% of job descriptions mention “computer science”.  There you have it, a degree in computer science is something “in demand” for getting into data science.

% of Data Science Positions Mentioning a Particular Skill on Indeed.com


Pulled this data by doing a search on indeed.com 11/2018


How important is SQL?

I’m frequently asked this question, and I was honestly surprised that SQL came in third behind Python and R in terms of skills. However, 51% of jobs do mention SQL.  So it is certainly desired for the majority of positions, but I expected it to rank higher.  Is it possible this skill is becoming assumed as a prerequisite? Or are companies figuring that SQL is easily learned and therefore not necessary to list on the job description? I wouldn’t mind a job where all the datasets were aggregated for me before data cleaning and applying machine learning, I’m just not sure how many of those jobs exist.  If you’re a data scientist, and you haven’t had to understand relational databases at any point, let me know. I’d love to hear about it.

A version of this article first appeared here

Share this article

Leave your comments

Post comment as a guest

0
terms and condition.
  • Alice Price

    Love your honest and efficient advices.

  • Charles Lou

    Thank you that was highly informative !

  • Brodie Leech

    Excellent !!!

  • Karl Lawford

    DS is different everywhere. At Google they build models, at Facebook they are data driven PMs.

  • Richard Sheppard

    Very informative and clears up a lot of confusion

  • Adrian Keister

    Great stuff! One place where data scientists sometimes don't need to work with databases is in the OT world of physical sensor data. Such data often contains a gigantic number of data points, and the overhead of a RDMS just gets in the way. More often, you might use a file format like tdms, from National Instruments.

  • kotrappa sirbi

    Thank you so much!! But I think project based learning using skills like Python/R/SQL will more beneficiary and advantages .

  • Xingsheng

    I would agree that sql is still an essential skill for a data scientist.

Share this article

Kristen Kehrer 

Tech Guru

Kristen is #8 LinkedIn Global Top Voice 2018 – Data Science & Analytics. She started her journey to becoming a Data Scientist without knowing it. She finished a BS in Mathematics in 2004 but wasn’t sure how she would be applying this education in industry. She then returned to academia for a Master’s Degree in Statistics, and knew that she wanted to be analyzing data, building models, and helping to guide business decisions. Since 2010, she has utilized Data Science across multiple industries, including the utilities, healthcare, and eCommerce. Prior to attaining her Master’s Degree, she was a high school math teacher, and have always enjoyed tutoring, coaching, and mentoring. Her passion is leveraging her experience with the end-to-end job search for Data Science positions to help others effectively market their skills to land a job in this field. The coaching she has personally received was invaluable to how she approached the job search and how she presented herself, she is so thrilled to share this expertise with others. Kristen is also a member of the Data Science Office Hours YouTube channel. When she is not doing Data Science, she can be found with her husband and two young children. She is also a mechanical keyboard hobbyist and aerialist.

   

Latest Articles

View all
  • Science
  • Technology
  • Companies
  • Environment
  • Global Economy
  • Finance
  • Politics
  • Society