What are the responsibilities and job description for the Senior Biostatistician position at Tbwa Chiat/Day Inc?
ID : 2025-8583)
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Axle is seeking a Senior Biostatistician, Pharmacoepidemiology to join our vibrant team at the National Institutes of Health (NIH) supporting the National Center for Advancing Translational Sciences (NCATS) located in Rockville, MD.
Benefits We Offer :
- Paid Time Off and Paid Holidays
- 401K match up to 5%
- Educational Benefits for Career Growth
- Employee Referral Bonus
- Flexible Spending Accounts :
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)
We are seeking a talented Senior Pharmacoepidemiologist to join our team to support projects at the NIH’s National Center for Advancing Translational Sciences (NCATS). In this role, you will collaborate with clinical and data scientists, methodologists, and software engineers to develop and execute exemplar causal inference studies. You will work as a subject matter expert to create a real-world evidence (RWE) methods decision tree; support master protocol development; and support development of gold-standard guides and methodologies for conducting best practices causal inference research. You will : design, execute, and analyze studies using the National Clinical Cohort Collaborative (N3C) data; review and recommend strategies for selecting study designs to answer causal inference questions; help establish, and implement appropriate analytic value sets.
The ideal candidate for the Senior Pharmacoepidemiologist position is a highly skilled professional with a Ph.D. in Pharmacoepidemiology, Epidemiology, Biostatistics, Causal Inference, or a related field. This person has experience with electronic health record and / or claims data and a strong understanding of observational study principles, including : missing data handling methods; temporal research questions (cross-sectional, longitudinal); causal contrast of interest (e.g., intent-to-treat, per-protocol); effect measure of interest (e.g., risk ratio, hazard ratio); and estimands (e.g., average treatment effect, average treatment effect in the treated) of interest. Your research experience includes one or more of the following : target trial emulation, sequential trial analysis, marginal structural models, longitudinal matching, G methods, or equivalent causal inference methods, realized in multiple primary-author publications. Fluency with coding languages and tools is expected (i.e., SQL, Python, and R).
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Disclaimer : The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills,
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