Data Scientist (Real World Evidence)

About the Role

• Contractor position supporting the Global Epidemiology group in Clinical Sciences.
• Contribution to the design and execution of pharmacoepidemiologic studies.
• Support characterization of descriptive epidemiology for diseases and indications.
• Contribution to regulatory submissions and responses.
• Performance of literature reviews for ongoing support and/or development of drugs and devices.

Key Responsibilities

• Evaluate, synthesize, and communicate epidemiology literature in written and presentation formats.
• Lead or contribute to the development of new evidence through study design, protocol development, and statistical analysis plans of various databases, including secondary data sources.
• Support departmental needs for contributing to and developing content for sections of risk management plans, benefit risk assessments, safety and regulatory deliverables.
• Understand the role of epidemiology in signal evaluation and its contribution to key safety and regulatory deliverables.
• Generate tables, listings, and graphs for compound projects.
• Participate in the validation and quality assurance of any output produced.
• Generate and review validated table, listing, and graph output meeting the needs of clinical projects.

Requirements & Tech Stack

• Real World Data (RWD) and Real World Evidence (RWE) experience.
• Support for AI related initiatives and new methodology capabilities.
• Support for obesity data analysis.
• Familiarity with health insurance claims, health records, and registry data.
• SQL, SAS, python (at least one required). SAS is preferred.
• Clear communication with stakeholders, comfortable presenting.
• Background in HEOR, outcome research, or safety outcomes.
• SAS program experience required.

Qualifications

• MS or PhD minimum education.
• MPH or MS with more than 2 years of experience OR PhD/MD/PharmD with experience in epidemiology, outcomes research, or a related discipline.
• Excellent understanding of epidemiologic data sources and methods, with a demonstrated ability to apply them.
• Experience with disease epidemiology (population sizing) globally and regionally using short-term studies/analyses.
• Preference given to individuals with industry experience.
• Preference for candidates with clinical experience.