Principal Product Manager - Experimentation
Confirmed live in the last 24 hours
Godaddy
Job Description
Location Details: United States, Remote
At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.
This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings.
This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands.
GoDaddy is not currently considering candidates for this role in California, Seattle, or NYC.
Join our team
GoDaddy's CTO organization runs one of the most sophisticated experimentation programs in e-commerce - spanning hundreds of A/B tests across commercial surfaces, a rigorous incremental revenue measurement methodology, and a growing portfolio of dynamic optimization capabilities. This program is on the critical path to a CTO key result: doubling experiment velocity and unlocking multi-million-dollar incremental revenue from surfaces newly onboarded to experimentation.
As a Principal Product Manager for Experimentation, you will lead the full stack - from A/B test design and guardrails to Finance alignment on experiment value, to expansion of the portfolio across paywalls, the customer homepage, AI assistant surfaces, and front-of-store experiences. A key part of this roadmap is GoDaddy's continuous experimentation engine — a multi-armed bandit platform that autonomously reallocates traffic to higher-performing strategies in real time, and which represents the next frontier of the experimentation program.
This is a high-visibility role with direct exposure to VP-level collaborators across Engineering, Finance, and eCommerce - and a mandate to raise the velocity and rigor of experimentation across the entire organization.
What you'll get to do...
- Own the product roadmap for GoDaddy's continuous experimentation engine: drive expansion to commercial surfaces (paywalls, customer homepage, AI assistant, front-of-store) and define the strategy for onboarding new business units to dynamic experimentation.
- Lead incremental-revenue methodology alignment with Finance to establish revenue impact that Finance can recognize; partner with senior leadership to define and standardize how experiment value is measured and reported.
- Define and enforce A/B testing guardrails, post-rollout durability monitoring, and cannibalization controls across the commercial experimentation portfolio.
- Partner with the experimentation platform team to translate business needs into platform capabilities: experiment types, cohort structures, scoring logic, metric definitions, and kill criteria.
- Drive experimentation velocity: set targets, remove blockers, reduce cycle time from experiment build to conclusive result, and track efficiency across the portfolio.
- Work closely with data engineering, business analysts, and Finance to ensure experiment analysis is statistically rigorous and commercially interpretable.
- Act as the primary PM interface for VP-level collaborators and cross-functional partners across engineering, eCommerce, front-of-store, pricing ML, business analytics, and data engineering on all matters related to the experimentation program.
- Define and maintain the scorecard for experiment readiness: intake and prioritization criteria, go/no-go decision rights, steering committee alignment, and collaborator sign-offs.
- Build and communicate the business case for experimentation investments, connecting platform capability to realized business impact.
Your experience should include...
- 5+ years of product management experience in a fast-paced e‑commerce or platform environment, with direct ownership of experimentation programs or growth platforms and responsibility for backlog prioritization, feature requirements, and agile execution.
- Hands-on expertise designing, running, and interpreting production experiments (A/B tests, multi‑armed bandits, or sequential testing), with a strong command of experimentation statistics including p‑values, confidence intervals, power analysis, sample sizing, and guardrail metric design.
- Proficiency in experimentation frameworks and performance metrics, including incremental revenue, conversion and attach rates, revenue per visitor, and post
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