RWE Data Analyst

Main responsibilities:

Provide a high level of expertise in employing cutting-edge analytical & computational approaches to drive evidence-based pharmaceutical product development; Use statistical, analytical, data management and computational skills to execute analyses of pre-existing data to investigate research questions in teamwork with colleagues from health economics and value assessment (HEVA), medical affairs, business operations & strategy (BO&S) and commercial product team; Require a strong background in statistics, statistical programming, observational research design, and experience in the pharmaceutical industry

• People: (1) Act as a subject matter expert in real world analysis; (2) Work with internal and external study lead to scope and execute real world studies and projects.
• Performance: (1) Responsible for independently conducting Data and Statistical analysis on projects and studies. These projects include, but are not limited to: (a) Characterizing disease epidemiology based on diagnostic code and/or treatment codes; (b) Assess study feasibility based on patient population(s) available for analysis; (c) Descriptive cohort analyses based on a limited number of outcomes; (2) Use statistical, analytical, data management and computational skills to execute analysis of pre-existing data to investigate research questions; (3) Develop computational and statistical methodologies in Advanced Analytics for RWE;
• Process: (1) Apply a broad array of capabilities spanning Biostatistics, mathematics, modelling, simulation, text-mining/NLP, data-mining to extract insights and be able to communicate and champion these efforts across the company; (2) Plan and deploy methodological standards, standardized processes, demos, and POCs for the company’s highest priority business needs; (3) Contribute to the design, development, and implementation of Sanofi’s data science architecture and ecosystem to guide decision-making and building foundational capabilities

About you

• Experience: 6+ years; High level proficiency in Python and/or pyspark. Experience with Real-World Data (RWD), demonstrated proficiency in working with diverse real-world data sources (e.g., electronic medical records, administrative claims).
• Soft skills: High level of interactive communication including challenges to conventional thinking as necessary; Proven teamwork and collaboration; Rapid response analytics; High energy responsiveness and commitment to meeting stakeholders’ needs; Excellent Written and verbal communication skills, collaboration, and interpersonal skills

• Education: Advanced degree in quantitative field such as Statistics, Biostatistics, Applied Mathematics or related field with 6 years of industry or academic experience.
• Languages: Excellent knowledge of English language (spoken and written)