Avoid common data science resume mistakes that weaken ATS performance, hide technical skills, and make projects harder for recruiters to scan. A strong STEM resume should be clear enough for applicant tracking systems and specific enough for hiring managers who scan for tools, methods, results, and technical evidence.
What to focus on
- Do not bury the most important data science resume keywords. Put relevant tools, methods, programming languages, lab techniques, coursework, and engineering skills in clear sections.
- Avoid vague bullets. Replace task lists with measurable outcomes, project scope, tools used, constraints, methods, and results.
- Do not use overly designed formatting that can confuse applicant tracking systems. Keep headings simple and use a clean STEM resume template.
- Do not send the same generic resume everywhere. Tailor your data science resume to the target role and match the job description honestly.
How My STEM Resume helps
My STEM Resume gives you ATS-friendly resume templates, guided technical sections, project-first formatting, AI-supported resume feedback, and a direct path to create a polished resume. Instead of forcing STEM experience into a generic resume layout, the builder helps you organize skills, education, projects, research, certifications, and work experience around the evidence recruiters need.
Build a stronger data science resume
Use the corresponding landing page for role-specific tips and then start your resume with a clean template.