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VP, Business Intelligence & Insights

Job in San Mateo, San Mateo County, California, 94409, USA
Listing for: Rakuten
Full Time position
Listed on 2026-02-22
Job specializations:
  • IT/Tech
    Business Systems/ Tech Analyst, Data Analyst, Data Science Manager
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Job Description

Rakuten International is a division of Rakuten Group, Inc., a Japanese global technology leader in services that empower individuals, communities, businesses and society. Headquartered in San Mateo, California with more than 4,000 employees worldwide, the Rakuten International business portfolio includes market leaders in e-commerce, digital marketing, advertising, communications and entertainment. We create products and services that provide exceptional value by aligning members and the businesses that want to engage them in a shared community.

Rakuten is the most rewarding way to shop, giving millions of members Cash Back when they buy from their favorite brands. As a leading shopping platform, Rakuten partners with thousands of top brands across apparel, beauty and wellness, grocery, travel, on-demand services, subscriptions, and dining, helping members save on everyday purchases. Since 1999, Rakuten members have earned more than $4.6 billion in Cash Back, making it the largest Cash Back platform of its kind.

Learn more at

Rakuten Rewards is creating a newVP, Business Intelligence & Insightsrole to centralize analytics and elevate it into an enterprise-levelinsight and decision-support functionreporting directly to the CEO Office.

As analytics platforms and AI increasingly automate reporting, competitive advantage comes fromjudgment, context, and clarity-not dashboards. This role exists to ensure Rakuten Rewards has asingle source of truthfor business performance and a senior leader who can translate data into actionable insights that shape strategy, prioritization, and investment decisions.

What You’ll Do Lead Enterprise Data & Insights Strategy
  • Owns Rewards’ enterprise data and insights strategy for executive and operational decision-making (business-facing): defining how performance is measured, interpreted, and used to drive decisions
  • Establish asingle, trusted performance narrativeacross Product, Marketing, Commercial, and Finance.
  • Define the enterprise analytics roadmap in close partnership with Data Platform and Engineering teams.
Elevate Executive Decision-Making
  • Serve as a trusted thought partner to the CEO and executive leadership team.
  • Translate complex data intoclear insights, trade-offs, and recommendationsthat inform strategic decisions.
  • Surface risks, inconsistencies, and blind spots-bringing intellectual rigor and honesty to leadership discussions.
Build & Lead a Centralized Insights Organization
  • Unify analytics teams currently embedded across functions into acentralized Business Intelligence & Insights organization.
  • Set enterprise standards for metrics, definitions, and performance interpretation.
  • Build a high-performing team known for business acumen, credibility, and influence-not reporting volume.
  • Act as a key partner with Product, Engineering, Finance, Marketing, and Sales to ensure data reporting/forecasts and insights for company, merchants and buyers are relevant, timely, and decision oriented and meet their ongoing business needs
  • Examples for Areas of Support:
    While this role is enterprise in scope, examples of the types of decisions and analyses this organization supports include but not exhaustive:
Marketing & Growth
  • Marketing Mix Modeling (MMM) and incrementality analysis to inform marketing investment allocation
  • Customer LTV, cohort, and payback analysis to guide acquisition and retention strategy
Commercial & Revenue
  • Company-level and merchant-level revenue performance insights and forecasting
  • Sales quota and target-setting analytics grounded in historical performance and pipeline dynamics
  • Performance insights that inform prioritization across merchants, categories, and partnerships
AI-Enabled, Human-Led Analytics
  • Define the business requirements, use cases, and success criteria for AI-enabled analytics in close partnership with the Data & AI Platform organization.
  • Partner with Platform teams to ensure analytics tools and capabilities are aligned to enterprise insight needs and executive decision workflows.
  • Leverage AI and automation to accelerate insight generation, while ensuring human judgment, business context, and leadership perspective guide interpretation.
  • Ensure…
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