Director, AI Experimentation & Measurement
140 Pfizer Inc · USA - NY - Headquarters
$162,900–$271,500from the description
Jul 20, 2026
USA - NY - Headquarters
Jul 22, 2026
What this job asks for AI summary
A director-level role responsible for building and owning the end-to-end measurement and experimentation function across a portfolio of AI initiatives within Pfizer's US Commercial organization. The work centers on setting pre-registered success criteria, designing statistically rigorous experiments, maintaining a prioritized learning agenda, and translating evidence into clear narratives for senior leadership. Suited to someone with deep causal-inference and experiment-design expertise who can also operate independently at an executive level.
Senior level · 8+ years · New York-Newark-Jersey City, NY-NJ-PA · Bachelor's required · Full-time
We read this from the posting text with AI. Skim the description below before ruling yourself out.
Why we read it this way (7)
The role title is 'Director' but the posting describes a senior individual-contributor function (build-from-scratch, owns a portfolio measurement function, no direct-report management language beyond 'oversee and guide the work of other colleagues') — classified as Senior rather than Staff or Principal, and mapped to 15-2051 (Data Scientists) given the primary day-to-day work is experimentation design, causal inference, statistical rigor, and AI/ML evaluation. 15-2031 (Operations Research Analysts) is a plausible runner-up given the portfolio-level measurement and decision-support framing.
The posting lists multiple possible locations (the salary range explicitly excludes Tampa, FL, and mentions 'multiple locations'). New York metro is used as the primary CBSA based on Pfizer US Commercial headquarters; the actual work location may differ.
Minimum experience requirement varies by degree: 8+ years (Bachelor's), 7+ years (Master's), 5+ years (PhD). The 8-year floor (Bachelor's) is used as the overall years minimum per schema rules.
Most required qualifications are framed as competencies (systems thinking, storytelling, independence) rather than named technologies or tools; only concrete named technical capabilities are captured in the skills list.
Regulated-industry measurement experience, provenance/auditability frameworks, and experience standing up an experimentation function from scratch are listed under Preferred Qualifications. Responsible AI frameworks is the only concrete named technical concept among them and is marked preferred accordingly.
The bonus target (20% of base) and long-term incentive eligibility are noted but not captured in the compensation fields, which reflect base salary only as quoted.
Ignored 2 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): experiment design, power analysis.
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