Associate Manager (RWE), Medical Analytics
Known for its scientific and operational excellence, Regeneron is a leading science-based biopharmaceutical company that discovers, invents, develops, manufactures, and commercializes medicines for the treatment of serious medical conditions. Regeneron commercializes medicines for eye diseases, high LDL-cholesterol, atopic dermatitis and a rare inflammatory condition and has product candidates in development in other areas of high unmet medical need, including rheumatoid arthritis, asthma, pain, cancer and infectious diseases.
The Associate Manager (RWE) within Medical Analytics will be the statistical and statistical programming lead responsible for product(s)/project(s) in regards to Medical Affairs activities with some guidance and/or direct supervision from senior Medical Analytics colleagues.
This role will lead the statistics, data science and statistical programming aspects and deliverables for Real World Evidence (RWE) work streams within Medical Affairs with some guidance and/or direct supervision from senior Medical Analytics and Health Economics and Outcomes Research (HEOR) colleagues. RWE work streams will include analyzing real-world data sources such as administrative claims data, electronic health records, surveys, and registries.
Together with Medical Affairs and HEOR colleagues, he/she will define future research questions, plan and execute statistical analysis, provide input into and align with the publications plan, and support Medical Affairs/HEOR needs. He/she will need strong communication skills to interpret, explain, and discuss results of complex statistical analyses to both technical and non-technical colleagues. Working in a dynamic team with a wide range of interfaces, the role requires both strategic and operational skills combining innovative statistical thinking with a strong sense of business acumen.
• Serve as the statistical and statistical programming lead for RWE for Regeneron products and projects, with independence and/or some guidance and/or supervision from senior Medical Analytics and HEOR colleagues. In some cases, serve as the technical expert in a particular statistical area or application.
Plan and Execute Statistical Analyses
• Author parts of and/or provide significant input into the Statistical Analysis Plan (SAP) using large, real-world datasets to comprehensively and unambiguously define the statistical analysis specifications, data derivations, and display shells to be generated in collaboration with key stakeholders.
• Perform statistical analyses using a RWE analytics platform, SAS and/or R to create analytic datasets, generate tables, listings, and figures for internal use as well as in presentations and publications.
• Ensure quality of deliverables through appropriate testing/validation and active review for completeness and accuracy (including developing and implementing a well documented validation plan).
Analyze RWE Data Sources
• Analyze large real-world data sources such as administrative claims databases (e.g. Truven Marketscan, Medicare, Medicaid), EHR data (e.g. Optum Humedica, Geisinger EHR data), survey data (e.g. NHANES, MEPS), and registries.
RWE Data Science and Statistical Programming
• Implement statistical methods (e.g. logistic regression, propensity scores, survival analysis, longitudinal mixed models) used to answer epidemiological, health-services, and HEOR questions
• Create analytic datasets by querying the large, real-world database
• Derive new variables using medical/diagnostic coding systems (e.g. ICD-9/ICD-10, CPT-4, HCPCS, Loinc codes) and complex algorithms (e.g. diagnosis codes and drug codes)
• Develop flexible and robust SAS macros to efficiently implement commonly-used methods or approaches
Teamwork and Communication
• Strong communication skills to understand/document the SAP requirements and explain/discuss implementation details of complex statistical analyses to both technical and non-technical audiences.
1. Experience in authoring parts of and/or providing significant input in SAPs using large, real-world datasets, implementing the SAP using SAS or R, ensuring quality via validation, and explaining implementation details to technical and non-technical audiences.
2. Experience in statistical programming methods as it relates to: real-world evidence generation in epidemiology, health-services research, and HEOR
1. MS/MPH in statistics/biostatistics/epidemiology or related discipline (see Educational Requirements/Experience for more information)
2. Expert knowledge of statistical programming methods using SAS or R to solve statistical problems.
3. At least 3 years of statistical programming experience with SAS or R working with large, real-world databases in the biotechnology, pharmaceutical or other healthcare industries.
This is an opportunity to join our select team that is already leading the way in the Pharmaceutical/Biotech industry. Apply today and learn more about Regeneron's unwavering commitment to combining good science & good business.
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Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability status, protected veteran status, or any other characteristic protected by law.