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We are the leader in RNAi therapeutics – a revolutionary approach with the potential to transform the lives of people with rare and common diseases. Built on Nobel Prize-winning science, Alnylam has delivered the breakthroughs that made RNAi therapeutics possible and are just at the beginning of what’s possible. Our deep pipeline, late-stage programs, and bold vision reflect our core values: fierce innovation, passion for excellence, purposeful urgency, open culture and commitment to people. We're proud to be a globally recognized top employer, where an authentic, inclusive culture and breakthrough thinking fuel one another.
Associate Director, Observational Data Analytics
Location
United States
Posted
94 days ago
Salary
$181.1K - $244.9K / year
Seniority
Lead
No structured requirement data.
Job Description
Associate Director, Observational Data Analytics
Alnylam Pharmaceuticals
This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Associate Director, Observational Methods and Analytics is focused on real-world and non-interventional methods and associated analysis to support execution of epidemiologic studies. Reporting to the Head of Epidemiology, the position provides support to Epidemiology and the broader clinical development organization, advising on epidemiologic methods, data analytic strategies, and supporting stakeholders in various activities utilizing real-world and other non-interventional data. This position carries out programming and statistical analysis in collaboration with epidemiologists/statisticians. This includes data coding, creation of algorithms, linkage of datasets, and use of statistical packages or platforms. This position is also expected to support and advise on innovative epidemiologic methods (e.g., causal inference methods) to address specific study objectives using observational data. Working with program epidemiologists, this position supports clinical development, Safety and Risk Management (SRM), and Clinical Development. The position will partner with Epidemiologists to manage relationships with internal and external stakeholders. Must be able to prioritize and manage work across multiple projects and vendors. Provides strong communication to ensure successful and timely project delivery. Additionally, this position will be expected to solve technical problems with experience and expertise. Summary of Key Responsibilities - Assist in development of study protocols and analyses plans leveraging large RWD sources (Claims and/or EMR) - Create analytical databases from data extracts to facilitate execution of study analyses - Conduct analyses consistent with methods set forth in study protocols and analysis plans - Produce tables and figures for discussions with other investigators, clients, and for study reports - Present results internally and to clients - Assist in preparation of study reports and other deliverables - Contribute to the development of innovative epidemiological methods and analytical capabilities to support Quantitative Science’s leadership role both internally and externally. Qualifications - PhD in epidemiology or other quantitative public health discipline (epidemiology, biostatistics, statistics, bioinformatics, economics) with 2 years of experience of conducting observational analytics for pharma industry, CRO, or academic institution. - Expert level proficiency in SAS or R, SQL. Proficiency in another programming language e.g., python also desirable. - Deep expertise analyzing RWE data sources including administrative claims data. Experience analyzing non-interventional data from registries or other sources is desirable. - Familiarity with relational databases and proficient understanding of claims and ancillary file layouts - Expert in applied epidemiologic methods including causal inference as well applied biostatistical methods as they pertain to the analysis of observational/non-interventional data including regression analysis (e.g., OLS, longitudinal, logistic, Cox, GLM/GEE), survival analyses (e.g., Kaplan-Meier, cumulative incidence, accelerated failure time models), methods for causal inference (e.g., propensity weighting, TMLE, G-estimation). - Capable of implementing the analytics for advanced epidemiology methods (e.g., IPW, clone censoring, negative control, quantitative bias analysis, clean room operations, and data simulation). - Excellent project management skills; can prioritize multiple tasks and goals to ensure timely completion. - Confident and competent when interacting with internal and external stakeholders. - Strong written/verbal communication skills. Highly effective at summarizing and presenting key considerations and evidence. Requirements - Strong communication skills to ensure successful project delivery. - Ability to solve technical problems with experience and expertise. Benefits - Comprehensive benefits including medical, dental, and vision coverage - Life and disability insurance - Lifestyle reimbursement program - Flexible spending and health savings accounts - 401(k) with a generous company match - Paid time off, wellness days, holidays, and two company-wide recharge breaks - Generous family resources and leave Company Description We are the leader in RNAi therapeutics – a revolutionary approach with the potential to transform the lives of people with rare and common diseases. Built on Nobel Prize-winning science, Alnylam has delivered the breakthroughs that made RNAi therapeutics possible and are just at the beginning of what’s possible. Our deep pipeline, late-stage programs, and bold vision reflect our core values: fierce innovation, passion for excellence, purposeful urgency, open culture and commitment to people. We're proud to be a globally recognized top employer, where an authentic, inclusive culture and breakthrough thinking fuel one another.
Job Requirements
- PhD in epidemiology or other quantitative public health discipline (epidemiology, biostatistics, statistics, bioinformatics, economics) with 2 years of experience of conducting observational analytics for pharma industry, CRO, or academic institution.
- Expert level proficiency in SAS or R, SQL. Proficiency in another programming language e.g., python also desirable.
- Deep expertise analyzing RWE data sources including administrative claims data. Experience analyzing non-interventional data from registries or other sources is desirable.
- Familiarity with relational databases and proficient understanding of claims and ancillary file layouts
- Expert in applied epidemiologic methods including causal inference as well applied biostatistical methods as they pertain to the analysis of observational/non-interventional data including regression analysis (e.g., OLS, longitudinal, logistic, Cox, GLM/GEE), survival analyses (e.g., Kaplan-Meier, cumulative incidence, accelerated failure time models), methods for causal inference (e.g., propensity weighting, TMLE, G-estimation).
- Capable of implementing the analytics for advanced epidemiology methods (e.g., IPW, clone censoring, negative control, quantitative bias analysis, clean room operations, and data simulation).
- Excellent project management skills; can prioritize multiple tasks and goals to ensure timely completion.
- Confident and competent when interacting with internal and external stakeholders.
- Strong written/verbal communication skills. Highly effective at summarizing and presenting key considerations and evidence.
- Strong communication skills to ensure successful project delivery.
- Ability to solve technical problems with experience and expertise.
Benefits
- Comprehensive benefits including medical, dental, and vision coverage
- Life and disability insurance
- Lifestyle reimbursement program
- Flexible spending and health savings accounts
- 401(k) with a generous company match
- Paid time off, wellness days, holidays, and two company-wide recharge breaks
- Generous family resources and leave
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