Application Guide
How to Apply for Staff Scientist - Causal Inference
at Recursion
🏢 About Recursion
Recursion is a unique TechBio company that combines biology with technology through its Recursion OS platform, generating massive proprietary datasets to advance medicine using machine learning. Unlike traditional biotech or tech companies, they operate at the intersection of biology, data science, and clinical development, making them ideal for those wanting to apply quantitative skills to real-world medical problems.
About This Role
As a Staff Scientist in Causal Inference, you'll apply statistical programming and causal inference methods to large-scale health datasets (claims, EHR, genomics) to uncover relationships between clinical factors and outcomes. This role directly impacts clinical decision-making by producing rigorous evidence that guides Recursion's drug development programs, bridging data science with real-world patient impact.
💡 A Day in the Life
A typical day involves analyzing large health datasets (e.g., claims or genomics data) using Python/R to apply causal inference methods, collaborating with clinical development teams to design studies, and validating machine-learning models to produce evidence for decision-making in Recursion's drug programs.
🚀 Application Tools
🎯 Who Recursion Is Looking For
- Has an advanced degree (PhD or MS) in statistics, biostatistics, epidemiology, or a related quantitative field, with at least 6 years of hands-on experience applying causal inference to observational health data.
- Demonstrates expertise in Python or R for statistical programming, with proven experience developing and validating machine-learning predictive models from real-world datasets like claims or EHR.
- Possesses strong applied statistics skills, including model fitting, inference from observational data, and experience working with genomics or clinical data in a biomedical context.
- Can collaborate effectively with cross-functional teams (clinical development, biometrics, computational biology) and communicate complex causal findings to non-technical stakeholders.
📝 Tips for Applying to Recursion
Highlight specific projects where you applied causal inference methods (e.g., propensity score matching, instrumental variables, difference-in-differences) to health insurance claims, EHR, or genomics data, quantifying impact on clinical decisions.
Tailor your resume to emphasize hands-on experience with large biological/clinical datasets and machine-learning model validation, as Recursion's platform relies on proprietary data and ML-driven insights.
Mention any experience working in a TechBio, biotech, or clinical research environment, as Recursion values candidates who understand the intersection of data science and drug development.
Include examples of collaborating with clinical or biometrics teams to produce evidence for decision-making, as the role requires building relationships across functions.
Research Recursion's pipeline (e.g., clinical-stage programs) and mention how your causal inference skills could address specific challenges in their work, showing you've done homework on their mission.
✉️ What to Emphasize in Your Cover Letter
["Explain how your causal inference expertise aligns with Recursion's use of large datasets (claims, EHR, genomics) to decode biology and improve clinical outcomes.", 'Provide a concise example of a past project where you applied statistical programming (Python/R) to observational data to infer relationships that influenced clinical or pre-clinical decisions.', 'Highlight your ability to work cross-functionally, citing experience with clinical development or biometrics teams to produce rigorous evidence.', "Express enthusiasm for Recursion's TechBio approach, linking your skills to their platform's goal of advancing medicine through machine learning and proprietary data."]
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Explore Recursion's Recursion OS platform and published research to understand how they integrate biological datasets with machine learning for drug discovery.
- → Review their clinical-stage programs and pipeline (e.g., via press releases or investor materials) to identify areas where causal inference might be applied.
- → Look into their team structure (e.g., computational biology, biometrics) to understand cross-functional dynamics and how this role fits in.
- → Check for recent publications or talks by Recursion scientists on causal inference or real-world data in biotech contexts.
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Submitting a generic application without tailoring to causal inference in health data or Recursion's TechBio focus—avoid emphasizing unrelated statistical fields.
- Failing to provide concrete examples of hands-on experience with Python/R for statistical programming on large datasets (claims, EHR, genomics).
- Overlooking the collaborative aspect—not showcasing ability to work with clinical or biometrics teams, as the role requires building relationships across functions.
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!