Design and implement innovative disease population modeling pipelines using rigorous deep learning approaches
Use SQL and Python to write accurate, understandable, reproducible, and production-quality methods
Understand healthcare data and the latest machine learning/AI research and suggest ways to incorporate this to improve our models
Collaborate with solutions and product teams to translate business needs into data-driven solutions
Provide guidance and mentorship to junior team members and lead technical reviews of models and pipelines

Requirements

PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Epidemiology, or related field (or equivalent practical experience)
5+ years of experience building machine learning or statistical models deployed in production environments
Strong proficiency in SQL and Python
Strong proficiency in statistical and machine learning fundamentals
Demonstrated ability to translate business priorities into data science products
Excellent oral and written communication

Benefits

Competitive salary + significant equity
Gain hands-on experience at a fast-growing company, with clear opportunities for career growth
Work alongside top-tier engineers, data scientists, and privacy experts

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

deep learningSQLPythonmachine learningstatistical modelsdata modelingdata-driven solutionsproduction-quality methodsepidemiologystatistical fundamentals

Soft Skills

collaborationmentorshipguidancecommunicationleadershiptechnical reviewsbusiness translationproblem-solvingteamworkadaptability

Certifications

PhD in Data SciencePhD in Computer SciencePhD in StatisticsPhD in Applied MathematicsPhD in Epidemiology