Creating a Data Science Resume for Career Switchers

Creating a Data Science Resume for Career Switchers

As a career switcher, I had no idea where to begin in my efforts to create a data science resume or how to incorporate my background in ecological field work. I’ve only ever needed a resume for one specific field for my career thus far. Thankfully, Kaggle hosted a virtual CareerCon last week and it helped me develop new strategies for tweaking my work experience to target data science.

William Chen, a Data Science Manager at Quora, led a session called How to Build a Compelling Data Science Portfolio & Resume that included tips for formatting a data science resume. William spoke directly to his experience reviewing data science portfolios. Major advice from his talk included:

  • Keep it concise. A one page resume with simple readability is recommended.
  • Include relevant coursework and order it accordingly, from most to least to relevant.
  • Mention your technical skills, and especially those included in the posting for a desired position.
  • Highlight projects and include results and references, like web links.
  • Avoid including impersonal projects such as homework assignments.
  • Tailor your experience toward the job and include relevant capstone projects and independent research if you don’t have direct data science work experience to mention.

Below I’ve included some of my own changes to my resume to take existing project experience I have in the realm of data analysis and tweak it to fit a data science resume.

First of all, here’s an overview visual of the format of a recent version of my resume tailored for a job in land management and my edited resume for data science. The quality of the text isn’t amazing, but this is mainly to show increased readability and concise, relevant content.

Comparison of environmental science resume (left) and newly edited data science resume (right).
Comparison of environmental science resume (left) and newly edited data science resume (right).

William Chen’s advice led me to get to the point about why I would be a good candidate for an opportunity in data science. This meant I had to get my message across quickly. Previously, my resume was a wall of text divided by education, work experience, and relevant community service. This format is dense and confusing and would be improper to send to a hiring official in response to a data science posting.

I broke down my data science resume into the categories of experience, education, projects, skills, and relevant coursework. In experience, I highlighted potentially relevant duties such as data collection, analysis, and visualization that show my personal connection to data science. Next, I cut down the text in my education section from my previous resume to reveal only my school, its location, my degree earned, and my enrollment dates. The projects section includes three research projects I worked on in my undergraduate career that involved data collection, analysis, and synthesis. Lastly, I included a section for skills and a section for relevant coursework.

No matter what your academic or work background, you can find ways to make a data science resume. William Chen’s advice brought me to the realization that I had relevant technical skills and project experience in environmental science that I could translate into a purposeful foundation for a job in data science. When you think about your qualifications outside the context of a specific career field, creating a data science resume becomes a simple task.