• Collaborates and works closely with cross-functional teams, including data analysts/engineers and business stakeholders, to understand their needs and gather requirements
• Cleans, transforms and pre-processes data to ensure data quality, consistency and compatibility for analysis
• Develops and implements data analysis plans to answer clinical and safety questions
• Applies analytical and/or statistical techniques to analyze data and generate insights on safety questions
• Visualizes data and results to share insights with technical and non-technical cross-functional stakeholders
• Interprets and communicates findings through reports, presentations and visualizations
• Stays up to date and compliant with the regulatory landscape related to drug safety and data analyses
• Works closely with PV CoE and other stakeholders, sharing knowledge and best practices within the broader safety and analytics teams.
• Strong understanding of data sources, such as clinical trial data, electronic health records, and other healthcare databases
• Proficiency in data pre-processing, cleaning and transformation techniques to ensure data quality and compatibility for analysis
• Knowledge of relevant analytical and statistical methodologies, such as regression analysis, survival analysis etc.
• Excellent problem-solving skills and the ability to derive meaningful insights from complex real-world data sets
• Excellent communication and presentation skills to effectively convey complex concepts and findings
• Ability to work collaboratively in cross-functional teams and manage multiple projects simultaneously
• Strong attention to detail and accuracy in data analysis and interpretation

Requirements:

• Bachelor's or Master's (preferred) degree in a relevant field, such as Biostatistics, Analytics, Engineering or related discipline.
• Minimum of 3-5 years of experience in data analysis, statistical modeling, and data visualization, preferably within the biopharma or healthcare industry.
• Experience applying statistical and analytical techniques, to analyze real world data
• Experience with Python or R or SAS and SQL required
• Working knowledge of visualization tools, such as Tableau or Power BI is preferred
• Experience or familiarity with the biopharma industry