Director, Data Science

Key Responsibilities

• 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
• Experience integrating AI into customer-facing products and internal workflows
• 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