Staff Scientist – Real World Evidence, Data Science

Responsibilities

• Define and execute long ‑ term RWE strategies across the Abbott Vascular portfolio, in collaboration with clinical, regulatory, medical affairs, and market access stakeholders.
• Translate clinical and economic evidence gaps into actionable strategies aligned with business priorities.
• Lead the design and execution of real ‑ world evidence, health economics, and digital health studies related to Abbott medical devices, using complex data sources such as electronic health records, insurance claims, imaging data, and hospital administrative/billing databases.
• Support data science initiatives to transform complex healthcare data into clinically actionable insights through machine learning, predictive modeling, and advanced phenotyping approaches.
• Lead analytic strategy and perform hands ‑ on programming to execute RWE studies using SQL, R, SAS, Python, or similar languages.
• Evaluate and mitigate technical risks in study designs.
• Manage data preparation, cohort construction, variable derivation, and analysis across diverse data types.
• Ensure adherence to data governance standards and privacy requirements.
• Provide technical oversight of programming logic and validation, partnering with data analysts and data engineers to ensure accuracy, reproducibility, and regulatory readiness.
• Lead and oversee development of RWE study protocols and reports, regulatory deliverables, conference presentations, and peer ‑ reviewed scientific manuscripts.
• Communicate with regulatory and reimbursement agencies on study design and results, translating complex analytical methods into clear, clinically meaningful scientific narratives.
• Mentor other scientists on dataset selection, study design, and presentation of results.
• Maintain strong and up ‑ to ‑ date knowledge of the clinical landscape in the coronary and peripheral vascular space.
• Monitor emerging evidence, clinical guidelines, competitive technologies, and unmet clinical needs to inform RWE study design, endpoint selection, and evidence generation strategy.
• Apply clinical context to interpret real ‑ world data results, assess relevance to intended use populations, and support regulatory and clinical decision ‑ making.
• Collaborate effectively with peers across biostatistics, clinical affairs, regulatory affairs, medical affairs, health economics, and R&D teams.
• Represent RWE and observational research perspectives in cross ‑ functional project teams and strategy discussions.
• Cultivate relationships with key opinion leaders in the industry, including academic researchers, data vendors, and clinical experts, as appropriate.

• Masters Degree (± 18 years)
• Preferred Minimum 9 years, Related work experience with a complete understanding of specified functional area.
• Comprehensive knowledge and application business concepts, procedures and practices.
• Uses in‑depth knowledge of business unit functions and cross group dependencies/ relationships.
• Is recognized as an expert in work group.
• Works on complex problems where analysis of situations or data requires an in‑depth evaluation of various factors.
• Exercises judgment within broadly defined practices and policies in selecting methods, techniques and evaluation criteria for obtaining results.
• Has broad knowledge of various technical alternatives and their potential impact on the business.
• PhD, DrPH, MS, or equivalent advanced degree in epidemiology, biostatistics, clinical research, public health, outcomes research, biomedical engineering, or a related discipline.
• 4 – 8 years of experience in real ‑ world evidence, observational research, outcomes research, or related analytical research roles in industry, academia, consulting, or government.
• Hands ‑ on experience working with real ‑ world data sources, such as electronic health records, administrative claims data, hospital billing data, registries, or similar large healthcare datasets.
• Deep knowledge in observational study design and epidemiologic methods, including cohort studies, definition of exposures and outcomes, confounding considerations, and sensitivity analyses.
• Experience in development of RWE study protocols, analysis plans, or study reports, with exposure to…