Senior Data Scientist I, Real World Evidence (RWE), Life Sciences R&D

What you'll do

• Design and deliver RWE analyses for pharma clients, translating research questions into actionable study plans.
• Derive real-world endpoints, develop reusable analytical code, and apply methods such as causal inference and survival analysis.
• Interpret and communicate findings, limitations, and recommendations to technical and non-technical stakeholders.

What they ask for

• Education in epidemiology, biostatistics, data science, public health, or a related field, with either a PhD and 2+ years of additional work experience or a master’s degree and 4+ years of additional work experience.
• Expert proficiency with observational real-world healthcare data and time-to-event methods, including survival analysis; proven experience executing RWD analytical studies.
• Proficiency in R and SQL, machine learning, LLM-based coding assistants, and agentic frameworks for analytical or scientific workflows.
• Experience interfacing with clients; strong written and verbal communication and project management skills.

Nice to have

• Experience in pharma or drug development, clinical trial design (particularly Phase II-III), or claims, EHR, or registry data.
• Experience configuring LLM-based tools or agentic workflows for scientific discovery; oncology guideline knowledge, molecular data analysis, or cloud platforms such as AWS, BigQuery, or Google Cloud Platform (GCP).

Pay

USD 120,000-$170,000 base salary; USD 130,000-$180,000 base salary

Tools

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

AI focus

Uses LLMs, agentic workflows, and other AI tools to accelerate code development, discovery, documentation, review, and insight generation; applies machine learning and LLM-based coding assistants to support analysis.