Data Scientist II

Role overview

A data scientist is needed to develop clinically grounded, interpretable AI and analytics solutions that support commercial, medical affairs, clinical research, and enterprise decision-making within a precision medicine diagnostics organization. The role combines applied data science, statistical modeling, machine learning, and generative AI, owning defined workstreams from problem framing through modeling, validation, documentation, deployment support, and stakeholder communication. Success requires strong quantitative judgment, reproducible development practices, and the ability to explain methods and limitations to both technical and non-technical audiences.

Responsibilities

- Own analytics and AI workstreams for next-best-action and field education capabilities, translating integrated data into actionable recommendations - Advance literature intelligence workflows including search, retrieval, synthesis, evaluation, and validation of AI-generated outputs - Develop interpretable machine learning, statistical, and generative AI solutions using structured and unstructured clinical, laboratory, commercial, and enterprise data - Build reproducible workflows and reusable components that progress from research prototypes into reliable applications and decision-support tools - Lead analytics research proposals, including cohort definition, analysis planning, modeling, interpretation, and communication of results - Support abstracts, presentations, and research reports while applying appropriate privacy, security, validation, and documentation practices - Perform exploratory analysis, feature engineering, model development, evaluation, and scenario analysis using Python or R and SQL

Requirements

- BS or MS degree in data science, computer science, statistics, biostatistics, bioinformatics, or a related quantitative field - 5+ years of experience in data science, machine learning, advanced analytics, or AI engineering, including 3+ years in healthcare, diagnostics, biotechnology, clinical research, life sciences, or another regulated environment - Strong hands-on proficiency in Python or R, SQL, and Git-based development workflows - Experience developing and validating predictive, descriptive, statistical, or machine learning models on real-world clinical, EHR, laboratory, research, or other complex longitudinal data - Ability to produce audit-ready documentation covering data lineage, methods, assumptions, testing, validation, and model limitations - Strong written and verbal communication and collaboration skills across technical, scientific, clinical, and business teams

Nice to have

- Experience with AI-enabled search, natural language processing, literature intelligence, retrieval-augmented generation, or document synthesis - Experience moving analytical prototypes into production workflows including testing, monitoring, and ongoing support - Familiarity with cloud data platforms, model lifecycle management, and modern MLOps tooling

Benefits and work setup

- Base salary range of $108,000 to $135,000 USD, with eligibility for discretionary bonuses and restricted stock units - Remote role within the United States only - Health and welfare benefits including a gym reimbursement program - 401(k) plan with company match - Employee stock purchase plan and pre-tax commuter benefits - Living donor recovery policy providing up to 30 days of paid leave annually for organ or bone marrow donation