Associate Director, Real World Evidence (RWE) Analytics

Job Title: Associate Director, Real World Evidence (RWE) Analytics

Location: Cambridge, MA or Morristown, NJ

About the Job

The successful Associate Director, Real World Evidence (RWE) Analytics will provide programming support and Senior oversight to implementation of analyses and studies in large databases (e.g. administrative claims, electronic health records). The individual in this role will work in close collaboration with health economics and value assessment (HEVA), medical affairs, business operations & strategy (BO&S) and commercial product teams to understand research questions and translate those into actionable items for the analytics team. These responsibilities require a strong background in data sciences, including statistics and programming. Experience leading studies and analyses that use observational research design and secondary data, experience with secondary data sources such as administrative claims and electronic health records in the US and experience in the pharmaceutical industry are required. Experience guiding more junior team members through the implementation of analyses is a must. This position will report to the RWE Team Leader.

We are an innovative global healthcare company, committed to transforming the lives of people with immune challenges, rare diseases and blood disorders, cancers, and neurological disorders. From R&D to sales, our talented teams work together, revolutionizing treatment, continually improving products, understanding unmet needs, and connecting communities. We chase the miracles of science every single day, pursuing progress to make a real impact on millions of patients around the world.

Main Responsibilities:

The Associate Director, RWE Analytics will be responsible for overseeing the implementation of analyses and studies and providing Senior support and direction to Data Analysts on the RWE team.

These projects include, but are not limited to:

• Assess study feasibility in a variety of data sources available for analysis, including new or less familiar data

• Propose and conduct exploratory analyses that allow deep understanding of a data source at hand (e.g., ability to generate insights and visualize output that allows researchers to make decisions about study feasibility and study design)

• Analyze data based on provided definitions using traditional programming or other digital applications

• Characterizing disease epidemiology, burden of disease, rates of pre-specified outcomes based on diagnostic codes and/or treatment codes using descriptive and comparative study designs

• Review relevant literature for methods, lists of codes or validated algorithms

• Create statistical analyses plans and table shells from study protocols

• Analysis of data using traditional programming or other digital applications Development of algorithms, such as lines of therapy for oncology Traditional modeling approaches, including regression and time to event analyses Reporting of the results in form of study tables, dashboards or slide deck

• Communicating results to stakeholders

About You

EDUCATIONAL BACKGROUND AND JOB-RELATED EXPERIENCE

​Education:

• ​BA/BS + 7 years of relevant experience OR MS/PhD + 5 years of relevant experience,

• Academic training in the areas of mathematics, statistics/biostatistics, statistical programming, observational research, epidemiology, health economics, or a related quantitative field

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Required ​Experience

• Experience programming in R, Python, and SQL

• Working knowledge of statistical methods

• Experience applying epidemiological methods

• Experience analyzing multiple sources of secondary patient data (e.g., electronic medical records, administrative claims)

Required Skills

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