The Structure of a Strong Biostatistics Resume

Before you even start writing, it’s critical to know what a strong biostatistics resume should include—and why each section matters.

Your resume isn’t just a list of past experiences. It’s a marketing document that gives hiring managers and recruiters exactly what they need to say “yes.”

For roles in biotech, pharma, public health, research consulting, or academia, here’s the framework I recommend (and personally use):

Key Sections to Include on Your Resume

✅ Skills

List your technical and domain-specific proficiencies. Think:

• Statistical software: R, SAS, STATA, Python, SQL

• Trial methodologies: clinical trial design, survival analysis, mixed models

• Standards: CDISC, SDTM, ADaM This is one of the first places recruiters and ATS software look—so don’t bury it.

✅ Experience

Highlight past roles, internships, or research assistantships. For each:

• Use action verbs

• Focus on outcomes or collaborations

• Connect your work to relevant domains (e.g., “Supported Phase II oncology trial through statistical programming in SAS”)

✅ Education

Include your degrees, certifications, and relevant coursework.
If you don’t have direct industry experience yet, your education section can carry more weight—so make it count.

✅ Projects

Add 1–2 substantial academic or independent projects that show your skills in action.
Did you work with real datasets? Use survival models? Collaborate across disciplines?
Put that here—this section is a goldmine for early-career applicants.

✅ Publications (If Applicable)

If you’ve co-authored a peer-reviewed paper, presented a poster at a conference, or written an abstract, include a short list of your most relevant work.
Stick to scientific publications that relate to your target industry or role.

Why This Resume Framework Works

When I first started reviewing resumes, I kept seeing the same issue: incredibly smart, qualified candidates were blending into the pile.

Then I started noticing what made the top 5% stand out.

It wasn’t always the degree level. It wasn’t even always the years of experience.

It was clarity, relevance, and structure.

When I applied for my current biostatistics role, I got interviews over PhDs with more experience. Why? Because my resume made it easy for the reviewer to see my strengths.

And that’s the whole point here:
Not to overdesign. Not to show off with complicated formatting.
But to deliver the right information in the right format for the person reading it—and for the ATS scanning it.

This structure works because it’s:

• Familiar to hiring managers

• Easy to parse in under 10 seconds

• Built for both humans and algorithms

Don’t fall into the trap of fancy templates or resume gimmicks. In data-driven, research-focused industries, consistency and professionalism beat creativity almost every time.

💡 Action Step: Sketch Your Resume Layout
Before you write a single bullet point, open a new document and create the five sections:

1. Skills

2. Experience

3. Education

4. Projects

5. Publications (if relevant)

Just drop in section headers for now. This gives you a clean foundation—and helps you stay focused as we dive into the details of each section later in the course.