Group Product Manager

Rakuten Rewards•San Mateo, CA

4d•$132,083 - $226,820•Remote

About The Position

Rakuten Rewards is building the measurement infrastructure that defines how we prove — and grow — our value with merchants. We are looking for a Group Product Manager to own the Merchant Measurement product agenda end-to-end: standardizing our impressions data foundation, validating our performance through third-party benchmarking and shadow studies, productizing incrementality testing at scale, and delivering a self-serve merchant data hub. This is both a hands-on and a people-leadership role. You will be the subject matter authority on merchant measurement in every room — with engineers, data scientists, merchants, and senior leadership — while also building and developing a small team of product managers who execute against the roadmap. You will report to the SVP of Product Management and partner closely with engineering, data science, commercial, and legal.

Requirements

8+ years of product management experience, with a significant portion in data infrastructure, ML platform, or applied AI product roles.
Bachelor's Degree Required
Deep understanding of the modern data stack — eventing systems, data pipelines, feature engineering, and how data flows from raw capture to AI-ready form.
Hands-on experience defining and shipping AI or ML platform capabilities: experiment management, model deployment infrastructure, feature stores, or monitoring frameworks.
Experience with graph databases or graph-based data models, and an understanding of how relationship-based data structures power recommendation and AI systems.
Track record of developing data products — pipelines, measurement platforms, reporting tools, or data sharing products — in close partnership with data engineering and data science.
Proven ability to lead a broad, complex portfolio — setting priorities clearly, managing dependencies across teams, and keeping cross-functional stakeholders aligned without requiring authority.
You distill technical complexity into clear narratives, and can calibrate your message for a CTO, a data scientist, and a merchant CMO in the same week.
You surface open questions early, move fast on follow-ups, and prefer to unblock rather than

Nice To Haves

Master's Degree Preferred
Experience in performance marketing measurement, affiliate analytics, or digital advertising attribution is a strong plus.
Background in economics, statistics, computer science, or a quantitative discipline
Familiarity with LLM-based productivity tooling and enterprise AI adoption patterns
Prior work in commerce, affiliate, or partner marketing environments

Responsibilities

Own the product strategy for Rakuten Rewards' data infrastructure — the systems that capture, validate, and route behavioral and transactional signals across member, merchant, and partner surfaces in real time.
Own the product for standardizing Rakuten's impressions and merchant measurement products —establishing it as the single source of truth for all downstream measurement, testing, and merchant-facing reporting.
Lead the development of unified member and merchant profiles — rich, continuously refreshed representations of behavior, preferences, intent, and performance that serve as the intelligence layer powering personalization, recommendations, and targeting across the platform.
Lead the strategy, roadmap, and delivery of Rakuten Rewards' ML platform — the foundational infrastructure that enables data science and engineering teams to build, experiment with, deploy, and monitor machine learning models at scale.
Enable incrementality testing at near-scale across top merchants and Lead Rakuten's engagement with third-party measurement platforms to benchmark performance
Define and deliver a self-serve, cloud-agnostic merchant data hub that gives merchants direct access to their performance data, with scalable data governance and permissioning developed in partnership with Commercial and Legal.
Serve as the internal authority on Data and AI product strategy — across executive reviews, merchant conversations, cross-functional planning, and external evaluations.
Drive alignment across engineering, data science, commercial, legal, and operations — proactively surfacing open questions and unblocking teams before issues compound.