Director, Data Science

Rakuten Group, Inc.

$156K — $291K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Strong foundation in machine learning, statistical modeling, and AI systems
  • Experience in deploying scalable models in production
  • Familiarity with Python, SQL, cloud platforms, and production ML tools
  • Ability to define strategy in ambiguous environments
  • Strong communication skills to influence stakeholders
  • Balance technical depth with business needs
  • Preferred: Experience in e-commerce and related domains
  • Preferred: Knowledge of LLM-based systems and generative AI solutions

Responsibilities

  • Lead and develop a high-performing centralized data science team
  • Shape and prioritize data science initiatives based on business outcomes
  • Translate business problems into actionable AI strategies
  • Ensure data science efforts yield measurable results
  • Serve as a strategic partner to senior leadership
  • Oversee delivery of machine learning and AI solutions from definition to production
  • Strengthen technical standards for applied AI across the organization

Benefits

  • Health, vision, and dental insurance
  • 401k matching
  • Paid time off (PTO)
  • Volunteer Time Off (VTO)
  • Discretionary bonus eligibility
Full Job Description
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

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.

USD $156,007.50 - $291,500.00 annually

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