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 organizational leadership, technical depth, and business ownership, with a mandate to scale high-impact AI solutions from concept to production. You will be responsible for setting the 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 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 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 for applied AI across the organization
Partner with engineering and platform teams to improve foundations for production AI, including experimentation, evaluation, model monitoring, and scalable infrastructure
Stay current with advances in ML and generative AI and guide thoughtful, pragmatic adoption of new capabilities
Qualifications:
Strong foundation in machine learning, statistical modeling, optimization, and/or AI systems
Experience leading the deployment and scaling of models in production environments
Familiarity with modern data and ML ecosystems (Python, SQL, cloud platforms, and production ML tooling)
Demonstrated ability to lead in ambiguous environments and define strategy from first principles
Strong communication skills with experience influencing senior stakeholders and cross-functional teams
Ability to balance technical depth with business pragmatism
Preferred: Experience in e-commerce, ad-tech, marketing science, recommender systems, or related domains
Preferred: Experience integrating AI into customer-facing products and internal workflows
Preferred: Experience with LLM-based systems, retrieval-augmented generation (RAG), and evaluation of generative AI solutions
Minimum Requirements:
10+ years of experience in data science, machine learning, or applied AI in industry; 15+ years 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
Bachelor's Degree Required; Master's Degree Preferred
Five Principles for Success
Our worldwide practices describe specific behaviors that make Rakuten unique and united across the world. We expect Rakuten employees to model these 5 Shugi Principles of Success.
Always improve, Always Advance - Only be satisfied with complete success - Kaizen
Passionately Professional - Take an uncompromising approach to your work and be determined to be the best
Hypothesize - Practice - Validate – Shikumika - Use the Rakuten Cycle to succeed in unknown territory
Maximize Customer Satisfaction - The greatest satisfaction for our teams is seeing their customers smile
Speed!! Speed!! Speed!! - Always be conscious of time - take charge, set clear goals, and engage your team
Rakuten provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type. Rakuten considers applicants for employment without regard to race, color, religion, age, sex, national origin, disability status, genetic information, protected veteran status, sexual orientation, gender, gender identity or expression, or any other characteristic protected by federal, state, provincial or local laws.