Entry level data science resume

Question

What should a resume look like for an entry level data scientist?

Answer

If you consider the venn diagram of data science below, an ideal candidate will have skills in three different areas:

  • math / stats
  • computer sci / software engineering
  • subject matter expertise / business acumen

The first two are more like "hard skill" that can be acquired in school or MOOCs, but the third one is hard to come by without actual experience. Therefore, when I screen entry-level data science resumes (entry level == either fresh out of school, or have less than 2 years of work experience), what I am looking for is more related to the first two areas.

Broadly:

  • Background or work experience that conveys that the candidate have good fundamentals with either software engineering or math/stats.

    Example: Bachelor or higher degree in STEM field, work experience as an data analyst or other types of data-related jobs (database administrator, quality engineer, business analyst…)

    Bonus: MS/PhD in highly quantitative field (maybe a narrower set of STEM fields - some STEM field doesn't require much math or coding), internship or short work experience in some data, math/stat, or software engineering -related capacity.

  • Previous school or work project and experiences that is related with dealing at least one area of the data pipeline (simplified pipeline may include data wrangling, descriptive statistical analysis, machine learning/predictive modeling, and data visualization). You have to demonstrate in your resume that you have previous projects that requires you to analyze data using things that are more sophisticated than Excel.

    Example: high-level project overview of a data-related projects that you have done before

    Bonus: a link to your github repo, or a demo-able data product, in which you build a data pipeline from scratch that demonstrates proficiency in more than one area.

  • Familiarity with scripting languages that are relevant to data science. Increasingly we are hoping our data scientists, and sometimes even or data analysts, to have prior exposure to Python and R. If you have experience with “production models” you may know Java and Scala as well.

    Borderline: Have analyzed data with SQL, or other point-and-click programs such as JMP, Minitab, SPSS, Stata...); have wrote some simple scripts in Python or R

    Example: Showed ability to run data munging, statistical tests and build predictive models using R (caret) or Python (statmodels, scikit-learn)

    Bonus: Hands-on experience with big data technologies (Hadoop, Hive, Spark…). It is hard to come by for fresh-out-of-school candidates though.

If you can satisfy the basic examples above, you should be a solid candidate for an entry-level data scientist.

Disclaimer:

  1. Views expressed in this answer are my own. While I am affiliated with my employer, I do not serve as the official spokesperson of our recruiting team.
  2. Keep in mind that the title "data scientist" means different things to different companies, so take this list at your own peril!

(Originally answered on quora: What should a resume look like for an entry level data scientist?)

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