Senior Manager, Data Science & Analytics

ROLE SUMMARY
Are you passionate about transforming data into actionable insights for marketing and commercial success? Do you thrive in a dynamic environment that blends data science, analytics, and commercial strategy for Pharma? Join our team as a Senior Manager, Data Science & Analytics, where you will lead the development and deployment of advanced analytics solutions to support strategic decisions across key commercial and business priorities. You'll leverage cutting-edge technologies-including AI, machine learning, Generative AI and cloud-based analytics platforms-to drive decisions and optimize outcomes across channels and customer segments. This global role offers the opportunity to collaborate with cross-functional teams, influence strategy, and shape the future of data-driven decision making.
The ideal candidate is an expert in data science with experience working in diverse and cross-functional teams, bridging the gap between data, technology, and people, with experience in advanced analytics and impact assessment using techniques like experimentation (A/B testing), observational analytics, and predictive modeling to deliver the promise of AI/ML to improve patients' lives.
ROLE RESPONSIBILITIES

• Lead the design, development, and implementation of advanced analytics and data science solutions using statistical and machine learning techniques.
• Drive the evolution of analytics processes for data integration, performance measurement, and decision support across commercial and business initiatives.
• Oversee experimentation frameworks (A/B testing, test-control design, causal inference approaches) to quantify impact and optimize business decisions.
• Serve as the subject matter expert for advanced analytics and data science, providing strategic guidance to senior commercial and business leaders.
• Collaborate with cross-functional teams (marketing, finance, IT, data engineering, product teams, agencies as applicable) to align analytics initiatives with business objectives and ensure seamless data integration.
• Lead and mentor a team of data scientists and analysts, fostering technical excellence and professional growth.
• Develop and maintain reusable analytics assets, custom data pipelines, and dashboards for performance tracking and visualization.
• Communicate complex analytical findings to non-technical stakeholders, translating data insights into actionable recommendations.
• Stay abreast of industry trends in advanced analytics, AI, Generative AI, and data science, proactively identifying opportunities for innovation.
• Lead planning and prioritization of analytics services and change management with cross functional stakeholders.
• Define evaluation and monitoring approaches for LLM/agent-assisted analytics (quality, reliability, bias, traceability) and promote responsible AI practices.

Technical skills and competencies:

• Strong strategic, conceptual and analytical thinker with the ability to understand analytics needs, leverage learnings from other industries and use sophisticated analytical tools and techniques to build effective solutions.
• Applied expertise in statistical modeling, machine learning, experimentation, forecasting, and optimization; ability to select the right technique based on business context and data limitations.
• Advanced proficiency in Python, R, SQL, and cloud analytics platforms (e.g., Azure, AWS, GCP).
• Applied knowledge of machine learning, deep learning, and statistical modeling across structured and unstructured data.
• Working knowledge of Generative AI and Agentic AI concepts (prompting patterns, tool use/function calling, orchestration basics, RAG fundamentals)

BASIC QUALIFICATIONS

• 9+ years of experience in advanced Analytics / Data Science, with experience delivering solutions for commercial, marketing, or business domains.
• 2+ years in a leadership role managing analytics teams and cross-functional projects. STEM degree (Statistics, Computer Science, Engineering, Mathematics, Economics) with quantitative emphasis.
• Expert proficiency in Python, R, SQL, and modern analytics platforms.
• Demonstrated experience in statistical analysis, machine learning, and optimization.
• Strong verbaland written communication skills; ability to influence and collaborate across teams.
• Applied knowledge of statistical analysis, experience with R, Python, Excel, etc.
• Strong background in optimization, mathematical modeling, machine learning, algorithms, and data structures, superior analytical skills required.
• Strong verbal and written communication skills.
• Demonstrated experience interfacing with other internal and external teams to incorporate their innovations and vice versa

PREFERRED QUALIFICATIONS

• Industry experience in healthcare / pharma / life sciences, marketing analytics, or commercial analytics.
• Consulting experience and proven project management skills.
  Experience with Bayesian statistics, cloud computing, and big data technologies.
• Exposure to Generative AI solutions (LLMs), including practical experience with retrieval-augmented generation (RAG), evaluation approaches, and responsible AI practices.
• Familiarity with agentic patterns such as multi-step workflow orchestration, tool-augmented LLMs, and human-in-the-loop decisioning

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