Senior Manager, Oncology Data Science, Hematology

Role Summary

Senior Manager of Data Science & Analytics supporting hematology, responsible for developing data-driven insights to inform commercial strategy, brand planning, and operational effectiveness. Must perform hands-on data analysis and collaborate with cross-functional teams to ensure data informs business-critical decisions for Adcetris and Elrexfio. Will manage data assets including claims, sales, and specialty pharmacy data, and integrate insights into the franchise’s strategic direction. Reports to the Senior Director of Data Science & Analytics within Pfizer’s Oncology Commercial Analytics team. Work Location: Hybrid.

Responsibilities

• Data Analysis and Insights Generation
  • Advanced Analytics: Develop and implement advanced analytics models, using techniques such as machine learning, predictive modeling, and statistical analytics, to drive insights into customer behavior, market trends, and product performance.
  • Secondary Data Analysis: Leverage multiple external data sources (e.g., claims data, specialty pharmacy data, non-retail sales) to generate actionable insights that address strategic business questions.
• Data Management and Governance
  • Data Asset Management: Partner with Commercial Information Management and data governance teams to ensure the proper stewardship of data, including the integration of new data assets to enhance decision-making.
  • Data Quality and Consistency: Ensure the quality, accuracy, and timeliness of data used for analysis by collaborating with IT, Marketing, and other cross-functional teams to maintain clean and reliable datasets.
  • Data Sourcing: Collaborate with the Director of Oncology Data Enablement to identify and assess relevant commercial data sources (e.g., Komodo Health, IQVIA, Symphony) that can be integrated into analytics projects to improve insights and decision-making capabilities.
• Targeting and Segmentation
  • Customer Segmentation: Apply advanced data science techniques to develop customer segmentation strategies that optimize targeting and resource allocation for marketing and sales teams.
  • Engagement Optimization: Analyze customer behavior and market data to develop insights that enhance engagement strategies and drive commercial success.
• Brand Performance and Market Insights
  • National-Level Reporting: Develop and maintain national-level brand performance reports, providing detailed insights into market trends, competitive dynamics, and product performance.
  • Launch Support: Provide analytical support during product launches, including competitive intelligence, market analysis, and performance tracking to ensure successful market entry.
  • Operational and Market Effectiveness: Analyze data to inform operational effectiveness and market performance, providing insights that optimize marketing strategies and sales operations.
  • Reporting and Dashboards: Create and manage executive-level reports and dashboards, ensuring that KPIs, market trends, and insights are effectively communicated to decision-makers.
• Cross-Functional Collaboration & Stakeholder Engagement
  • Cross-Functional Partnership: Work closely with teams (e.g., Marketing, Market Research Insights, Forecasting, Finance) to integrate data insights into broader strategic initiatives and support decision-making.
  • Stakeholder Communication: Present complex analytical insights to senior leadership, translating data into clear and actionable recommendations that support business-critical decisions.
• Innovation and Continuous Improvement
  • Process Improvement: Continuously identify opportunities to improve data analytics methodologies, processes, and tools to enhance the efficiency and accuracy of insights.
  • Emerging Trends: Stay current with industry trends and emerging data science techniques, incorporating innovative approaches into data analysis to drive better business outcomes.
• Vendor and Resource Management
  • Vendor Collaboration: Manage relationships with external vendors and data providers, ensuring timely delivery of high-quality data and insights that meet the franchise’s needs.
  • Budget and Resource Allocation: Collaborate with Data Science & Analytics leadership to manage budgets and allocate resources effectively to support franchise data science and analytics efforts.

Qualifications

• Required:
  • Education: Bachelor’s degree in data science, analytics, mathematics, biological or physical sciences, statistics, business, or a related field.
  • Experience: Minimum of 6+ years in data science, analytics, or commercial operations, with at least 5+ years in the pharmaceutical or biopharmaceutical industry. Post-graduate education can substitute for part of the experience.
  • Technical Skills: Proficiency in Python, R, SQL, and data visualization platforms (e.g., Tableau, Power BI).
  • Cross-Functional Experience: Experience working with marketing, sales, and IT to integrate data insights into commercial strategies.
• Preferred:
  • Oncology Expertise: Experience in oncology with understanding of market dynamics, customer behavior, and competitive trends.
  • Technical Skills: Experience with machine learning and predictive modeling techniques.
  • Advanced Degree: MBA or related advanced degree.

Skills

• Analytical Mindset: Strong analytical and problem-solving skills to develop data-driven solutions.
• Strategic Thinking: Ability to translate complex data into actionable forecasts that drive decisions.
• Communication: Excellent verbal and written communication to present insights to commercial leaders and cross-functional teams.
• Project Management: Ability to manage multiple projects, prioritize, and meet deadlines in a fast-paced environment.

Education

• Bachelor’s degree in data science, analytics, mathematics, biological or physical sciences, statistics, business, or related field.