Lead the development and execution of statistical analysis plans (SAPs) for large-scale real-world evidence (RWE) studies.
Oversee and mentor junior analysts, reviewing work for accuracy, quality, and consistency.
Establish and maintain strong, trusted relationships with client counterparts.
Lead the development of new tools and automated workflows to improve the efficiency and impact of RWD analysis.
Lead the creation of sophisticated data visualizations, dashboards, and other reporting tools.
Drive the continuous improvement of data management, analysis methodologies, and reporting standards.
Collaborate with internal teams (data scientists, epidemiologists, statisticians) and external stakeholders to integrate data from multiple sources.
Requirements
Minimum 7-9 years of experience in RWD analytics, biostatistics, epidemiology, or a related field, with at least 3 years in a leadership or consultancy role.
Proven track record in managing complex observational research projects in the life sciences or healthcare sector, particularly with large health databases (claims data, EMR, etc.).
Expertise in SAS programming; advanced proficiency in SQL, R, Python, and other relevant programming languages (e.g., MATLAB, Hadoop, Spark).
Experience working with cloud platforms like AWS, Azure, or Google Cloud is strongly preferred.
Expertise in advanced data visualization tools such as Tableau, Power BI, or D3.js.
Deep understanding of the US healthcare system, health insurance claims data, and electronic medical records (EMR).
Experience applying advanced statistical methods and machine learning techniques to large healthcare datasets.
Familiarity with database management, data wrangling, and data integration techniques.