Director, Data Science

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 4000 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 .

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 tradeoffs progress and impact

AI & Machine Learning Execution

• Own the endtoend 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 productionready 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

• Bachelors Degree Required; Masters 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

At the time of posting Rakuten expects the base compensation for this role to be within the range shown below. Individual compensation will vary based on job-related factors including the skills qualifications and experience of the successful candidate as well as business need and geographic location. The successful applicant for this role will be eligible for discretionary bonus health vision dental insurance 401k matching PTO Volunteer Time Off (VTO) and other employee benefits as the company implements.