Sr. Director, Data Science Products Lead

ROLE PURPOSE

Lead the Data Science Products team: the team that turns proven data science capabilities into owned, governed, reusable products and evolves them over time (v1.0 → N). The portfolio is the measurement, optimization, and forecasting engine behind commercial investment decisions across USA and International: marketing mix and incrementality measurement, promotional and media investment optimization, and forecasting. Each product line runs on sophisticated production pipelines and is on a deliberate path from analyst-run engines to agentic solutions. The Lead builds and runs the portfolio through hands-on technical Product Owners, establishes the operating model that lets Data Science and analytics teams pull the products through for themselves with consistency and rigor, and is accountable for the technical quality of the models and the agents alike.

KEY RESPONSIBILITIES

• Portfolio leadership — Own the strategy, roadmap, and health of the full product portfolio across measurement, optimization, forecasting and more; allocate scarce capacity across product lines; inform what to build once and reuse versus what stays bespoke.

• Operating model & CoE authority — Stand up and run the global/shared model: methodology standards, the shared codebase, intake and prioritization, quality standards, and best-practice forums, so the team operates as a true CoE that enables scale and consistency across markets.

• Measurement standards — Own the standard for how commercial impact is measured, versioned, and validated across the portfolio, including how incrementality tests and experiments are used to calibrate and validate the models, so that numbers entering investment decisions and leadership reviews are trusted and developed with rigor.

• Technical leadership — Set and review modeling methodology across the portfolio: Bayesian and causal marketing mix modeling, constrained optimization, incrementality and experiment design, and time-series and hierarchical forecasting. Apply engineering and architectural standards across product lines; ensure a common, well-governed GitHub codebase and sound MLOps practice: model registry, versioning, monitoring, retraining, and reproducible pipelines.

• Agentic products — Lead the evolution of each product line from analyst-run engine to agentic solution: agents that answer investment and forecast questions in natural language, run scenarios, explain drivers, and propose allocations within guardrails, grounded in the production pipelines. Own the portfolio standards for how these are built: grounding in model outputs, evaluation, guardrails, cost, traceability, and human oversight.

• Lifecycle & hand-offs — Interface with Applied Intelligence (0 → v1.0 incubation) so proven capabilities graduate cleanly into product ownership, and with Operations & Delivery and Business-Aligned so products are run and tailored at scale.

• Senior stakeholder leadership — Be the senior point of contact for the USA and International commercial leadership the products serve, and for Finance and brand leadership where measurement and forecasts enter investment and planning decisions; ensure equitable, consistent service across both markets and represent the portfolio with executive stakeholders.

• People & capability — Hire, develop, and retain a small, dense team of senior technical Product Owners; steward headcount carefully, funding new product lines without hollowing out established ones.

BASIC QUALIFICATIONS

• Education & experience — Bachelor’s degree in a quantitative discipline with 12+ years of relevant experience; OR Master’s degree with 10+ years; OR PhD with 7+ years.

• Machine learning — 8+ years hands-on building and deploying statistical and machine learning models in production, with demonstrated depth in causal inference and marketing mix or incrementality modeling (Bayesian methods, adstock and saturation, hierarchical pooling, response-curve estimation and constrained optimization) and working fluency in time-series forecasting (hierarchical, probabilistic, or ensemble methods). Able to review model design in code and credibly challenge it.

• Agentic & generative AI — Hands-on experience with LLM-based and agentic systems: has built, or directly led the build of, tool-using agents or natural-language interfaces over analytical models and pipelines, including evaluation, guardrails, and human-in-the-loop controls. Able to set the standard by which agentic solutions are built on production models, and to judge when an agentic approach is and is not warranted.

• ML engineering & MLOps — Strong, current Python and SQL; proficiency with Git/GitHub, code review, CI/CD, and automated testing; experience running MLOps at scale (model registry, versioning, monitoring and drift detection, retraining, reproducible pipelines) on cloud data and ML platforms such as Databricks, Snowflake, or AWS.

• Technical leadership — 5+ years leading senior technical talent, product portfolios, or platform/CoE organizations that other teams depend on.

• Federated enablement — Demonstrated success enabling federated delivery: building reusable, configurable products that distributed teams adopt rather than route around.

• Domain — Experience with pharmaceutical or healthcare commercial data (promotion, media, Rx, field activity, financial planning) and the measurement, optimization, or forecasting built on it.

• Travel — Ability to travel occasionally (approximately 10% or less).

PREFERRED QUALIFICATIONS

• PhD and/or MBA.

• Experience supporting both USA and International commercial organizations.

• Experience standing up a product operating model, platform team, or center of excellence from an existing service organization.

• Experience applying agentic AI in a regulated environment, including evaluation frameworks for accuracy and compliance, and a point of view on how AI-assisted and agentic engineering changes team design and delivery economics.

• Experience designing incrementality tests and experiments (geo tests, holdouts) and using them to calibrate marketing mix and response models.

• Experience partnering with Finance and brand leadership on investment allocation and forecast-based planning.

• Experience managing the interface between incubation/innovation teams and product/run organizations.

 
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.

Other Job Details:

• Last Date to Apply for Job: November 18, 2026.
• Ability to travel based on business needs
• This position is hybrid and requires working onsite 2 to 3 days per week
  

 

 

The annual base salary for this position ranges from $230,900.00 to $384,800.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 25.0% 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.

 

 

 

 

 

 

This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview.

 

 

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

 

 

 

 

 

 

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.

 

 

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