You work with teams of data scientists and engineers to pull vast data sets together and transform valuable info into actionable insights. You formulate data-driven decisions to improve the company’s growth, direction, and engagement.
But sometimes, your resume might still feel tricky to navigate. What programming languages or modeling types do you include, and how do you make sure your resume template stands out?
Folks like you have requested our advice for years on optimizing their resumes: Check out these three data science manager resume templates and seasoned tips to gain the best of the best!
Related resume examples
What Matters Most: Your Skills Section & Job Experience
Recruiters want you to go beyond the surface-level skills found on any data science resume and give them specifics. Don’t just say “strategizing” when you can reference Agile methodologies and propensity modeling instead.
Be specific about niche programming languages or software you use to make things happen. List names rather than programming categories, and think critically about what showcases your strongest points. Are we talking recommendation engines or production models?
Many people make the mistake of being too broad or generic with their skills, instead of showing their full capabilities with solid examples like these:
9 top data science manager skills
- Keras
- NumPy
- Redshift
- NoSQL
- Git
- Propensity Modeling
- Agile Methodologies
- Market Segmentation
- Productionizing Models
Sample data science manager work experience bullet points
While your skills list should be highly technical and focus primarily on hard skills like MySQL and Pandas, your experience section is a great place to show how you assist others with your knowledge.
Your work history should show the path you took to advance to management, including your ability to connect with others and make a positive impact within a group while sharing your knowledge of propensity modeling and Flask.
Speaking of impact, you’ll need to measure it whenever you share your accomplishments. Good resumes use quantifiable data to back your claims—otherwise, you sacrifice invaluable credibility in terms of your ability to create results with your models and methodologies!
Here are some samples:
- Built ETL infrastructures and delivered data to Redshift, which increased stakeholder decision-making output by 42%
- Owned energy production reporting using Python and SQL, saving over 31 hours of manual work hours each week
- Supervised data science and data engineering teams in developing marketing mix models that led to an ROI improvement of 21% on digital market spend within 13 months
- Identified duplications across team projects and reduced them by 92% by increasing coordination and compatibility
- Recommended over 114 actionable steps within the first year that improved automation by 7% and boosted profits by 9%
Top 5 Tips for Your Data Science Manager Resume
- Demonstrate ownership
- Every managerial role requires a strong drive and an unshakeable sense of project ownership. You’re the go-to for many other data scientists, so show recruiters that you’re experienced in helping them meet strategy and profit goals.
- Really stress the metrics
- Use more than one per experience point, if you can! The more quantifiable data you can use to measure your data-driven ability to predict industry demands and then program accordingly, the better. Just make sure each point remains sleek and readable.
- Don’t get too fancy
- While you may feel compelled to balance out your technical data science skills with a super-friendly color palette, don’t get carried away. A small pop of color can convey approachability but be minimalistic!
- Software specialization is key
- Go beyond general stuff like “Python” and specify which niches you’ve settled into. Including names like Pandas and Flask will show depth of knowledge and demonstrate your ability to adapt to unique demands.
- Don’t forget your cover letter
- You can’t afford to ramble in your resume, so take note of any key points that could use some extra background. Save these for your data science manager cover letter to provide fresh information and a bigger picture of the impact you left with your awesome ETL infrastructures or advanced data reports.
Frequently Asked Questions
- Do I have to customize every time?
- Yes, but it’s not bad! All you really need to do is revisit the job description and comb for skills you have, programming languages you’re a pro at, and company profit or labor reduction goals similar to projects you’ve already completed. Reflect these in your resume.
- What fonts should I use?
- Recruiters will initially only spend a few seconds skimming your resume, so make it as easy as possible for them to read your stuff. Use clear, simple fonts and avoid anything that looks cartoonish or unprofessional so that your resume looks as clean as your data.
- How do I show my versatility?
- Show versatility through context. Think of as many different types of initiatives as you can from your work history: Did you develop an extra-awesome forest model? What about that amazing infrastructure you built? Think big!
