Senior Data Analyst

Job Responsibilities Develop a strong understanding of internal stakeholders’ data and analytical needs, with a focus on customer-facing leadership models. Advocate for the integration of local customer insights into strategic planning and resource allocation decisions. Partner with US Sales Force Operations to drive key business processes and collaborate on joint initiatives. Identify, prioritize, and lead the development and deployment of new analytical tools and capabilities across the organization. Foster a culture of continuous improvement, encouraging innovation, testing, and adoption of new solutions. Introduce advanced analytical practices to establish and maintain a competitive advantage. Access and leverage information from diverse tools and data sources. Communicate findings effectively through clear presentations and multiple communication channels. Apply advanced technical expertise (e.g., data modeling, deep knowledge of core datasets) and share best practices within the team. Demonstrate strong cross-functional understanding and collaboration, ensuring alignment with colleagues’ work. Stay current with external trends and leading-edge analytic capabilities within and beyond the pharmaceutical sector, and identify opportunities for application within the business.Job Requirements Bachelor’s degree in a quantitative discipline (Engineering, Operations Research, Management Science, Economics, Statistics, Applied Math, Computer Science, or Data Science) from an accredited institution is required; advanced degree (Master’s, MBA, PhD) preferred. Minimum 2+ years of experience in Pharmaceutical, Biotech, or Healthcare analytics or secondary data analysis. At least 5 years of experience applying advanced statistical methods and procedures to large, complex datasets. 4+ years of hands-on experience with PySpark, Python, R, and SQL. Familiarity with platforms such as Databricks. Working knowledge of data visualization tools (Power BI, MicroStrategy, Tableau, QlikView, D3.js, or similar) preferred. Proficiency with MS Office, particularly Excel and PowerPoint. Strong experience in analyzing large longitudinal data sources (Claims, EMR, and other patient-level datasets). Prior exposure to IQVIA datasets. Ability to extract, interpret, and clearly communicate insights from complex analyses. Strong organizational and time management skills. Proven expertise in handling and analyzing a wide range of large-scale secondary transactional databases. Solid background in statistical analysis and modeling.

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