Director, Data Science (San Mateo)
AI summary of the role
Rakuten Rewards seeks a Director of Data Science to lead the centralized data science organization, reporting to the CTO.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Lead and grow a high-performing centralized data science organization, including managing managers and hiring top talent
- Translate ambiguous business problems into clear, actionable AI and machine learning strategies
- Own end-to-end delivery of ML and generative AI solutions from problem definition through production deployment and iteration
- Set technical direction and quality standards for scalable ML, optimization, and GenAI systems across campaign forecasting, optimization, and member experience
What you’ll bring
- 10+ years of experience in data science, machine learning, or applied AI in industry (15+ preferred)
- 5+ years of leadership experience, including managing managers and building scaled teams
- Proven track record of delivering measurable business impact through production-grade ML/AI systems
- Strong foundation in machine learning, statistical modeling, optimization, and/or AI systems
Technologies
Python · SQL · cloud platforms · production ML tooling · LLM · retrieval-augmented generation · generative AI · machine learning · statistical modeling · optimization
About Rakuten
Cash-back and loyalty platform connecting 15M+ US shoppers with 3,500+ retail partners; subsidiary of Rakuten Group (TYO: 4755)
Public · 2000–5000 people
Source and classification
Internal deployment & tooling · Evidence for this classification:
Leadership & Business Impact Lead and grow a high-performing centralized data science organization, including managing managers, hiring top talent, and fostering a strong, accountable culture Help shape data science strategy and prioritize initiatives based on feasibility and expected business outcomes Translate ambiguous business problems into clear, actionable AI and machine learning strategies Own problem framing, success metrics, and end to end accountability to ensure data science efforts translate into measurable business outcomes Serve as a trusted partner to senior leaders, clearly communicating strategy, trade‑offs, progress, and impact AI & Machine Learning Execution Own the end‑to‑end delivery and effectiveness of machine learning and generative AI solutions, ensuring successful progression from problem definition through production deployment, monitoring, and
More from the job description
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.com. Job Summary: Rakuten Rewards is seeking a Director of Data Science to lead our centralized data science organization, influence strategy and drive execution of machine learning and generative AI initiatives that deliver measurable, company-wide business impact. Reporting directly to the CTO, this role combines organization [... source excerpt omitted ...] technical vision, mentoring a high-performing team, and ensuring that our data science efforts directly translate into competitive advantages and improved member experiences. Key Responsibilities: Organizational Leadership & Business Impact Lead and grow a high-performing centralized data science organization, including managing managers, hiring top talent, and fostering a strong, accountable culture Help shape data science strategy and prioritize initiatives based on feasibility and expected business outcomes Translate ambiguous business problems into clear, actionable AI and machine learning strategies Own problem framing, success metrics, and end to end accountability to ensu [... source excerpt omitted ...] Learning Execution Own the end‑to‑end delivery and effectiveness of machine learning and generative AI solutions, ensuring successful progression from problem definition through production deployment, monitoring, and iteration. Set technical direction and quality standards for scalable ML, optimization, and GenAI systems that deliver measurable impact across domains such as campaign forecasting, campaign optimization, and member experience optimization Ensure solutions are production‑ready, observable, and continuously improved, with a strong focus on reliability and business effectiveness Foundations, Platforms & Innovation Strengthen best practices and technical standards f
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