Principal Product Manager, Experimentation & Digital Analytics

## Principal Product Manager, Experimentation & Digital Analytics Apply remote type:
Hybrid locations:
Bethesda, MD:
San Francisco, CA:
Palo Alto, CA:
San Jose, CA:
Seattle, WAtime type:
Full time posted on:
Posted Todayjob requisition :
R0065265
** Why Join GEICO?
** At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive on relentless innovation to exceed our customers' expectations while making a real impact on local communities nationwide.

Founded in 1936, GEICO is a member of the Berkshire Hathaway family of companies and one of the largest auto insurers in the United States. When you join our company, we want you to feel valued, supported, and proud to work here. That's why we offer the GEICO Pledge:
Great Company, Great Culture, Great Rewards, and Great Careers.

GEICO, subsidiary of Berkshire Hathaway and a leader in Auto insurance and other product lines, is on a multi-year technology transformation journey to reimagine the customer experience in the Insurance industry by removing friction across customers, partners, marketplace, segments, and channels and building a world-class digital experience powered by modern data and AI.As part of this transformation, we are looking for an accomplished, customer-obsessed, results-oriented Principal Product Manager to own our experimentation and digital analytics platforms and drive a company-wide culture of experimentation and data-driven decision making.

This role is central to GEICO's ability to learn faster, act on evidence, and deliver greater customer and business impact in service of GEICO's growth and retention objectives.

As a Principal Product Manager, you will own the tools and platforms that power experimentation, digital behavioral analytics, and insight generation across GEICO. You will define and drive the strategy for these platforms, championing their adoption across product, design, engineering, marketing, and analytics teams, and enabling those teams to self-serve, automate, and scale their own experimentation and analysis. You will be responsible for increasing the velocity, quality, and business value of experimentation, analysis, and insight generation enterprise-wide — while ensuring rigor, statistical integrity, and trust in the results.

You will collaborate closely with cross-functional teams, including engineering, design, marketing, and analytics, to deliver high-impact platform capabilities that drive business growth and customer satisfaction. You must be comfortable communicating and influencing at all levels of the organization.

Additionally, you bring a strong quantitative and statistical foundation combined with prior experience building or leading experimentation programs, and you are energized by turning a nascent or fragmented practice into a scaled, self-service, insight-driven capability.

You are also an AI-native product manager who uses AI tools daily to move faster — from synthesizing research and generating experiment hypotheses to accelerating analysis and prototyping platform capabilities — and who sees applying AI to automate and scale insight generation itself as core to this role, not a side skill. This is a hybrid position, requiring on-site presence 2-3 days a week at one of the following locations:  Palo Alto, CA;
Seattle, WA;
Bethesda, MD.
** Job Responsibilities
*** Own the product vision, strategy, and roadmap for GEICO's experimentation and digital analytics platforms, aligned to GEICO's growth, retention, and digital transformation goals.
* Drive adoption of experimentation and digital analytics tools across product, design, engineering, marketing, and analytics teams, removing friction and building trust in the platforms and their outputs.
* Enable teams to self-service and automate experiment design, instrumentation, execution, analysis, and reporting, reducing dependency on manual or ad hoc processes.
* Define and evolve the standards, guardrails, and governance for experimentation (e.g. statistical methodology, sample size and power,…