Director, AI Experimentation & Measurement

Pfizer US Commercial is scaling a portfolio of AI initiatives, each launched as an experiment measured against a real-world baseline. The value of that portfolio depends on one thing: a shared, credible definition of what good looks like plus the evidence to prove we are reaching it.

We are hiring a Director of Experimentation & Measurement to own that definition end to end. This is not a scorekeeping role. You will decide what is worth proving next, design the experiment that proves it, set the bar for success before the work begins, and tell the story of what the evidence means to the people making the biggest decisions. You areequal parts systems thinker, experiment designer, and storyteller, with the rigor to make sure the story is true.

This is a build-from-scratch role for someone who can see across a whole portfolio, frame the questions that matter most, and hold the independence to say when a result does not clear the bar.

What you will own

1. Success criteria & proof standards. Own the portfolio-wide standard for what counts as proof1efined before work begins, not afterresults land. Draft and socialize pre-registered success criteria for each initiative (primary KPIs, guardrails, minimum detectable effect, read windows). Maintain a shared measurement playbook (matched controls, power calculations, blinded review,backtesting where appropriate).

2. Portfolio learning agenda. Prioritize what the portfolio must prove next1and in whatsequence evidence compounds. Maintain a ranked learning agenda across initiatives and recommend the next proof point per initiative.

3. Experiment design & statistical rigor. Review experiment designs: control arms, audience matching, read windows, confounders, data leakage risks. Run power analysis and flag underpowered orungradeable designs beforelaunch.

4. Evidence narrative for senior leaders. Produce evidenceread memos on a fixed cadence: what was tested, what wasobserved, what it means, what is recommended. Synthesize across initiatives into one portfolio story1not a patchwork of disconnected scorecards.

5. Measurement integrity & bias controls. Guard against failure modes that quietly invalidate results: moving goalposts; letting thepeople a system is meant to outperform grade it; acting before pre-registered proof exists. Escalate when a read is notgradeable.

6. Evidence governance & readout cadence. Run evidence read sessions at pre-registered dates; own continue / adjust / stop recommendations with rationale; track whether recommendations are acted on.

Key stakeholders & accountability

Partners with initiative facilitators on criteria, design, and readouts. Influences BU Presidents and proxies by helping define their success criteria and reporting back whether evidence meets the bar. Reports results and implications to USLT and Chief Commercial Office as portfolio executive sponsors.

What werequire

Experience: 8+ yrs (Bachelor's) 3+ yrs (Master's) 5+ yrs (PhD), spanning experimentation, measurement science, causal inference, or a quantitatively rigorous discipline 1 paired with strategy or product-facing work.

Required Qualifications:

-Bachelor's degree required with 8+ years of relevant experience spanning experimentation, measurement science, causal inference, or a quantitatively rigorous discipline 1 paired with strategy or product-facing work.
- Systemsthinking: sees across an entire portfolio, frames the questions that matter most, and designs how proof compounds over time rather thanoptimizing one test at a time.
- Storytelling and executivepresence: turns a rigorous, technical result into a clear, persuasive narrative that shapes senior decisions.
- Experiment design and causal credibility: has designed and defended controlled experiments at enterprise scale: power analysis, matched controls, quasi-experimental methods, pre-registration.
- Independence and spine: able to tell a senior stakeholder thata result does not clear the bar, and make it stick.
- AI fluency: evaluates AI/ML and generative systems credibly: what a real performance signal looks like versus a plausible artifact.

Preferred Qualifications:

- Regulated-industry measurement experience.
- Provenance, auditability, andresponsible-AI evaluation frameworks.
- Experience standing up an experimentation or evidence function from scratch.

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: July 26, 2026.

• Ability to travel based on business needs

• This position is hybrid and requires working onsite 2 to 3 days per week

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

Candidates must be authorized to be employed in the U.S. by any employer.

U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.