Senior Manager, Data Science & Analytics

Role Summary:

The Senior Manager of Data Science & Analytics supporting Elrexfio is responsible for developing data-driven insights to inform commercial strategy, brand planning, and operational effectiveness. This role requires hands-on data analysis and close collaboration with cross-functional teams to ensure data is leveraged to support business-critical decisions for Elrexfio. The Senior Manager will manage various data assets, including claims, sales, and specialty pharmacy data, and will work across oncology commercial analytics and commercial teams to integrate insights into the franchise’s strategic direction. This position will report to the Senior Director of Data Science & Analytics within Pfizer’s Oncology Commercial Analytics team.

Key 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 key performance indicators (KPIs), market trends, and insights are effectively communicated to decision-makers.

Cross-Functional Collaboration & Stakeholder Engagement

• Cross-Functional Partnership: Work closely with other 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.

Basic Qualifications:

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

• Experience: Minimum of 7+ years of experience in data science, analytics, or commercial operations, with at least 5+ years in the pharmaceutical or biopharmaceutical industry. Post-graduate education can substitute for a portion of the work experience requirement.

• Technical Skills: Proficiency in data analysis tools such as Python, R, SQL, and data visualization platforms (e.g., Tableau, Power BI).

• Cross-Functional Experience: Experience working with cross-functional teams, including marketing, sales, and IT, to integrate data insights into commercial strategies.

• Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.

Preferred Qualifications:

• Oncology Expertise: Experience working in oncology, with a deep understanding of market dynamics, customer behavior, and competitive trends in the oncology space.

• Technical Skills: Experience with machine learning and predictive modeling techniques is highly desirable.

• Advanced Degree: MBA or advanced degree in a related field is preferred.

Skills and Competencies:

• Analytical Mindset: Strong analytical and problem-solving skills, with the ability to develop data-driven solutions to complex business challenges.

• Strategic Thinking: Ability to think critically and strategically, translating complex data into actionable forecasts that drive business decisions.

• Communication: Excellent verbal and written communication skills, with the ability to present complex data insights to commercial leaders and cross-functional teams in a clear and actionable manner

• Project Management: Proven ability to manage multiple projects simultaneously, prioritize competing demands, and meet deadlines in a fast-paced environment.

 

Other Job Details:

• Last Day to Apply: July 16, 2025
• Additional Locations: Washington – Bothell, California - San Francisco, Illinois - Chicago, Massachusetts - Kendall Square, New York - New York City and Mexico - Mexico City.
• Work Location Assignment: Hybrid; 2-3 days onsite/week with Pfizer’s Log In for Your Day requirements.​
• Eligible for employee referral bonus​

#CommercialAnalytics #ProductLaunch #Oncology #DataScience

The annual base salary for this position ranges from $120,800.00 to $201,400.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.

Relocation assistance may be available based on business needs and/or eligibility.

Marketing and Market Research

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