Director, Data Science

Director, Data Science

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Director, Data Science based in United States.

This role offers the opportunity to lead a high-impact data science organization responsible for building intelligent systems that enhance customer experiences, optimize operations, and drive business growth. The Director of Data Science will define the machine learning strategy, guide technical innovation, and translate advanced analytics into measurable outcomes. Working across consumer experiences, delivery intelligence, and advertising solutions, this leader will shape the future of large-scale ML applications. The role combines strategic leadership with hands-on technical involvement, allowing the successful candidate to influence architecture, mentor teams, and contribute directly to production systems. This position requires a strong balance of business understanding, technical expertise, and leadership ability within a fast-paced technology environment. The ideal candidate will thrive in an autonomous setting where experimentation, innovation, and impactful data-driven decisions are highly valued.

Accountabilities:

The Director of Data Science will lead the development and execution of machine learning strategies across multiple business areas, ensuring that data science initiatives deliver meaningful customer and operational value. This role will manage talented teams, establish technical standards, and collaborate with executives and cross-functional partners to drive innovation.

• Own the end-to-end data science roadmap, aligning machine learning priorities with business goals, measurable outcomes, and strategic initiatives.
• Provide technical leadership, mentorship, and guidance to Data Scientists and ML Engineers while promoting best practices in model development, evaluation, and deployment.
• Partner with senior leadership, Product, Engineering, and Business teams to integrate ML capabilities into product and operational strategies.
• Build a culture of experimentation by defining measurement frameworks, improving A/B testing practices, and connecting model performance to business impact.
• Lead the development of advanced consumer-facing ML solutions, including search ranking, query understanding, personalization, recommendations, and behavioral modeling.
• Drive delivery intelligence initiatives through predictive modeling for ETA optimization, demand forecasting, routing, fleet utilization, and operational efficiency.
• Develop and optimize advertising intelligence solutions, including ranking systems, relevance models, attribution pipelines, bid optimization, and audience targeting.
• Architect scalable machine learning platforms and collaborate with engineering teams to bring models into production environments.
• Evaluate emerging technologies and methodologies to improve ML capabilities, including LLMs, transformers, contextual models, and causal inference approaches.
• Build and retain high-performing data science teams while fostering collaboration, innovation, and continuous improvement.

Requirements:

The ideal candidate is an experienced data science leader with a strong background in machine learning, product analytics, and team management. They should have proven experience delivering ML solutions at scale, strong technical depth, and the ability to connect advanced models with business outcomes.

• 8+ years of experience in applied data science or machine learning, including at least 3 years managing data science or engineering teams.
• Experience leading data science initiatives within fast-paced technology, e-commerce, marketplace, retail, or consumer-focused environments.
• Proven expertise in machine learning architectures, including two-tower retrieval systems, transformers, LLMs, contextual bandits, graph neural networks, and causal or uplift modeling.
• Strong experience with search, recommendation, ranking, or personalization systems, including relevance modeling and multi-objective optimization.
• Hands-on programming experience with Python and the ability to contribute to model development, experimentation pipelines, and production systems.
• Experience with large-scale ML infrastructure, including feature stores, model registries, real-time serving systems, and experimentation platforms.
• Strong product intuition and business acumen with the ability to connect ML improvements to revenue, customer satisfaction, and operational metrics.
• Demonstrated ability to communicate complex technical concepts clearly to executives and cross-functional stakeholders.
• Track record of building, mentoring, and retaining diverse, high-performing technical teams.

Preferred Qualifications:

• Experience in consumer marketplaces, quick-commerce, grocery, retail, or advertising technology environments.
• Familiarity with retail media measurement standards and privacy-preserving attribution approaches.
• Experience building real-time personalization systems and streaming feature pipelines.
• Familiarity with platforms such as Databricks and Snowflake.
• Publications or conference presentations at recognized machine learning or data science conferences.

Benefits:

• Competitive base salary range of $215,000 - $275,000, depending on skills, experience, qualifications, and market factors.
• Eligibility for annual performance-based bonus opportunities.
• Participation in an equity incentive plan.
• Comprehensive medical, dental, and vision insurance.
• 401(k) retirement savings plan.
• Health Savings Account (HSA) or Flexible Spending Account (FSA) eligibility.
• Short-term and long-term disability insurance.
• Group life insurance coverage.
• Flexible paid time off.
• Employee discounts and membership benefits.
• Fitness reimbursement program.
• Employee Assistance Program with wellness and mental health resources.
• Opportunity to work on high-impact machine learning initiatives with significant autonomy and visibility.
• Ability to shape foundational AI and ML systems in a rapidly evolving technology environment.