Data Scientist II, Real World Evidence, Life Sciences R&D

What you'll do

• Design and execute RWE research plans, derive clinical endpoints, and apply statistical methods such as causal inference and survival analysis.
• Interpret and communicate study findings and limitations; prepare reports, client deliverables, and, where appropriate, manuscripts or conference materials.
• Develop reusable analytical code and incorporate LLMs, agentic workflows, and other AI tools into research processes.

What they ask for

• Education in epidemiology, biostatistics, data science, public health, or a related field: PhD, or master’s degree plus 2+ years of additional work experience.
• Experience analyzing observational real-world healthcare data, including survival analysis, and executing RWD studies.
• Proficiency in R and SQL, statistical tools and packages, and applying machine learning and LLM-based assistants or agentic frameworks to analysis, code review, or documentation.
• Client-facing communication experience and good software engineering practices, including version control, modular code, and documentation.

Nice to have

• Experience in pharma or drug development, clinical trial design, claims/EHR/registry data, oncology guidelines, or biomarker/molecular data.
• Experience adapting LLMs for scientific work or using AWS, BigQuery, or Google Cloud Platform (GCP).

Pay

$100,000-$140,000 USD base salary; $110,000-$150,000 USD base salary

Tools

R, SQL, Claude Code, Copilot, Cursor, AWS, BigQuery, Google Cloud Platform (GCP)

AI focus

Use LLMs, agentic workflows, machine learning, and other AI tools to accelerate code development, discovery, documentation, review, data analysis, and insight generation.