Improving Your Junior Data Scientist Resume
If you’re looking for entry-level data analytics or data science jobs and you’d like to improve your resume, this is for you.
I’m writing this because I see a lot of junior data science resumes that combine long lists of programming languages and other tools with limited detail about what the individual is actually working on.
My goal is to help you write a resume that makes it easier for potential employers to connect the dots between their needs and your skills. And for data analysis and data science jobs, that means going into a lot of detail about your experiences doing statistical analysis and coding and less detail about other areas.
Here’s what I think should be on your resume, how you should talk about it, and what you should leave out.
What to Include (Briefly)
These are topics to include but not make the focus of your resume.
Relevant Coursework and Certifications: If you're a student or recent grad, list a few key courses in probability, statistics, or computer science, if you have those. If you majored or minored in math, statistics, or computer science, include that regardless of how long ago you graduated. If you have technical certifications, list them as well.
Extracurricular Activities: For students with limited work experience, mention leadership roles or significant activities like sports, writing for the school paper, etc. Omit this if you graduated more than a couple of years ago.
Non-Data Work Experience: Briefly list this, going into more detail if you gained relevant subject matter expertise for jobs you’re applying to or transferable skills like writing or managing people. If you've worked full-time in non-data roles, this should occupy a larger section of your resume than if your work experience is part-time or summer employment.
What to Emphasize
These are what you’ll go into the most detail about because they’re the most directly-related to the kind of work you’ll be doing in a future data analytics or data science job.
Professional Data Experience: Paid data analytics experience, if you have it.
Data Projects: Projects you've done independently or for classes.
What to Omit
I’d suggest leaving these off entirely.
Niche Academic Research Details: Mention publications or conference presentations, but describe your research in terms accessible to those outside your field. Have a separate CV for research-focused roles.
Lists of Programming Languages/Software: If you want to show you know something, find a way to talk in your resume about how you’ve used it. There’s such a huge range in what people mean by proficiency in a particular language that it’s not useful to list it with no context.
Statements of Purpose: Save explanations of who you are for tailored cover letters.
How To Talk About Your Data Experience
When describing your data analytics work, provide concrete details from the following areas:
Tools used (languages, packages)
Methods used (descriptive statistics, regressions, modeling techniques)
Outputs created (papers, graphs, dashboards)
Context (the problem you were solving, who it was for, impact of your work)
Good coding practices (using git, writing documentation, creating reusable modules, etc.)
You don't need to include all of these details for every data project. But specificity helps employers connect the dots between your experience and their needs. This is also how you can demonstrate proficiency in particular tools and languages — by providing concrete examples of how you've used them.
And make sure you can speak knowledgeably about everything on your resume. For instance, if you mention using a random forest model, be prepared to explain in an interview how that model works and why you chose it.
What Else to Include
A link to your GitHub account: And if you’re not on GitHub, and you’re applying to jobs asking for experience in R or Python, seriously consider getting on GitHub! I wrote here about improving Jupyter-notebook GitHub repositories.
Information that’s specific to the job you’re applying for: For instance, if you’re applying for a data analysis job at a health care company, you might list “health economics” in your education section. Or if the job listing includes a particular tool that you’ve used, make sure you include it somewhere on your resume and describe how you’ve used it.
By following these suggestions, you'll make it easier for employers to understand your background and connect it to what they’re looking for.