Manager, Analytics

The Global Commercial Analytics (GCA) team within the Chief Marketing Office (CMO) organization is dedicated to transforming data into actionable intelligence, enabling the business to remain competitive and innovative in a data-driven world.  We play a pivotal role in extracting insights from large and complex datasets to drive strategic decision-making. Collaborating closely with various subject matter experts across various fields, our team leverages advanced statistical analysis, machine learning techniques, and data visualization tools to uncover patterns, trends, and correlations within the data. Additionally, we are dedicated to delivering new, innovative capabilities by deploying cutting-edge Machine learning algorithms and artificial intelligence techniques to solve complex problems and create value.

As a hands-on Manager, Analytics within Commercial Decision Analytics, you will design, build, analytics solutions that optimize field force sizing, territory alignment, and commercial ROI across brands and markets. You will collaborate closely with Commercial, Sales Leadership, and Insights teams to transform data into actionable recommendations, deliver clear visualizations and business-ready presentations, and support MMM (Marketing Mix Modeling) in pharma contexts. This is an individual contributor role—not a people manager—ideal for someone who thrives on building, analyzing, and storytelling with data.

Field Force Sizing & Optimization

• Build analytical frameworks to determine optimal rep counts, structures, and deployment by market/brand/therapeutic area.

• Develop models for coverage, reach, frequency, and workload-driven territory design.

• Support scenario planning/simulation to evaluate alignment strategies and their impact on KPIs.

Territory Alignment

• Execute end-to-end territory alignment of workflows using potential, workload, and segmentation data.

• Maintain assignment rules, constraints, and performance baselines for territory changes.

Commercial ROI & MMM

• Contribute to pharma MMM (e.g., regression/Bayesian models with adstock/carryover) to quantify the impact of field, digital, email, media.

• Build ROI calculators and budget allocation recommendations for launch and established brands.

Analytics & Visualization

• Develop Tableau/ PowerBI dashboards and ad hoc reports that translate complex analysis into actionable insights for senior stakeholders.

• Build data pipelines and self-service assets in Dataiku; author queries in SQL; implement analyses in Python.

Data Management & Quality

• Ensure data integrity, freshness, and documentation across CRM, sales, claim/prescription, and market datasets.

• Contribute to data governance and standardization of metrics/definitions.

Stakeholder Collaboration & Storytelling

• Partner with Commercial, Sales, and Insights teams to understand requirements and present findings clearly, including recommendations and trade-offs.

• Develop business-ready presentations in PowerPoint synthesizing insights and next-best actions.

Cross-Functional Collaboration

• Work closely with Analytics Engineering to ensure the data ecosystem is conducive for data science modeling purposes.

• Partner with Digital teams to enhance data science capabilities, aligning efforts to leverage digital data sources effectively.

• Foster collaboration with other teams to ensure seamless integration of data science initiatives across the organization's infrastructure, promoting efficiency and effectiveness in leveraging data for informed decision-making

Education & Experience:

• Bachelor's/Master's in Statistics, Data Science, Engineering, Economics, or related quantitative field.

• Experience: 5–8 years in commercial Pharma analytics or Sales/Marketing analytics, with hands-on exposure to Field Force/Territory analytics and MMM.

Skills:

• Tableau / Power BI, SQL, Python, Excel (advanced), PowerPoint (executive storytelling)

• Experience with both traditional SQL and modern NoSQL data stores including SQL, and large-scale distributed systems such as Hadoop and or working in Snowflake/Databricks

• Communication: Excellent verbal/written skills to elicit requirements, explain methodology, and present insights to senior business leaders.

• Experience with supporting commercial strategies and tactics, experience in pharmaceutical or healthcare industry is preferred.

Preferred/Good-to-Have

• Knowledge of Statistical modeling and ML Techniques

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.