We are a large, enterprise-scale digital commerce, consumer technology, and AI-driven analytics organization serving millions of customers across multiple markets. The company operates across digital platforms, customer experience, product innovation, marketing technology, supply chain intelligence, personalization, pricing optimization, and enterprise data products.
This is the type of environment where data science is not limited to reporting or isolated modeling work. Data science is a core business function that influences how the company understands customers, improves digital experiences, forecasts demand, optimizes revenue, strengthens operations, and makes smarter enterprise decisions.
The organization is continuing to invest heavily in artificial intelligence, machine learning, predictive analytics, experimentation, customer intelligence, and data-powered product development. As the business grows, leadership is seeking a strategic data science leader who can guide advanced analytics initiatives, build scalable modeling capabilities, and turn complex data into measurable business value.
The Director of Data Science will lead a team responsible for developing and scaling data science solutions across key business areas. This includes predictive modeling, customer segmentation, recommendation systems, pricing intelligence, marketing analytics, forecasting, experimentation, personalization, operational optimization, and AI-enabled decision support.
This role requires a leader who can operate at both the strategic and technical levels. The ideal candidate will be comfortable advising executives, partnering with product and engineering teams, guiding data scientists, and ensuring models are not only technically strong but also practical, explainable, scalable, and tied to real business outcomes.
The selected candidate will play a major role in shaping the company’s data science roadmap and helping the organization move from insight generation to intelligent action. This is a high-impact leadership opportunity for someone who understands how to build data science capabilities inside a large, fast-moving, customer-focused enterprise.
• Lead the strategy, development, and execution of enterprise data science initiatives across customer experience, digital product, marketing, revenue growth, operations, and business performance.
• Build and manage advanced analytics models, including predictive models, machine learning algorithms, customer segmentation, churn prediction, lifetime value models, recommendation systems, demand forecasting, pricing models, and personalization solutions.
• Partner with executive leadership to identify high-value business opportunities where data science can improve decision-making, efficiency, customer engagement, and revenue performance.
• Lead a team of data scientists, machine learning specialists, analysts, and cross-functional contributors while promoting strong technical standards and business alignment.
• Translate complex business problems into clear analytical frameworks, modeling strategies, and measurable project outcomes.
• Collaborate closely with Product, Engineering, Data Engineering, Marketing, Finance, Operations, Customer Experience, and Strategy teams to deploy scalable data science solutions.
• Oversee model development, validation, testing, deployment, monitoring, and continuous improvement.
• Establish best practices for experimentation, A/B testing, causal analysis, model governance, feature engineering, documentation, and performance measurement.
• Ensure data science work is practical, explainable, ethical, and aligned with business priorities.
• Guide the use of AI and machine learning to improve personalization, customer insights, forecasting accuracy, operational planning, and digital platform performance.
• Develop executive-ready insights, recommendations, and performance narratives that clearly connect technical work to business value.
• Evaluate new tools, technologies, data sources, and analytical methods that can strengthen the company’s data science maturity.
• Support hiring, coaching, mentoring, and career development for data science team members.
• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or a related quantitative field required.
• Master’s degree or PhD in a quantitative discipline is strongly preferred.
• 10+ years of progressive experience in data science, machine learning, advanced analytics, predictive modeling, or applied AI.
• 5+ years of experience leading data science teams, analytics teams, machine learning teams, or cross-functional technical teams.
• Experience working within a large enterprise, digital commerce platform, consumer technology company, SaaS organization, retail technology company, financial technology company, marketplace business, or data-driven product environment preferred.
• Strong hands-on background with statistical modeling, machine learning, forecasting, optimization, experimentation, and data-driven decision science.
• Proficiency with tools and languages such as Python, R, SQL, Spark, Databricks, Snowflake, BigQuery, AWS, Azure, GCP, or similar modern data platforms.
• Experience deploying machine learning models into production environments in partnership with engineering or MLOps teams.
• Strong understanding of data pipelines, model monitoring, feature stores, data quality, model explainability, and responsible AI practices.
• Proven ability to connect data science initiatives to business results such as revenue growth, customer retention, conversion improvement, cost reduction, efficiency gains, and customer experience improvement.
• Experience presenting technical concepts and recommendations to senior executives in a clear, business-focused manner.
• Strategic and analytical leader with the ability to identify where data science can create the most business value.
• Strong technical judgment with the ability to guide complex modeling work without losing sight of practical business application.
• Excellent communicator who can explain machine learning, AI, and statistical concepts to both technical and non-technical audiences.
• Strong leadership presence with the confidence to advise executives and influence enterprise priorities.
• Highly collaborative with the ability to work across product, engineering, marketing, finance, operations, and executive teams.
• Comfortable balancing innovation with governance, speed with accuracy, and experimentation with operational reliability.
• Strong problem-solving mindset with the ability to simplify complex data challenges into actionable decisions.
• Ability to mentor senior and junior data scientists while building a high-performance, business-oriented team culture.
• Comfortable working in a large, fast-paced organization where priorities shift, and data science must remain connected to measurable outcomes.
• High integrity and strong judgment around data privacy, model fairness, ethical AI, and responsible use of customer data.
The Director of Data Science will serve as a strategic partner to executive leadership by helping the company identify, prioritize, and execute data science opportunities that support growth, customer experience, and operational excellence.
This role will help shape the organization’s AI and machine learning roadmap, including where predictive analytics, automation, personalization, experimentation, and advanced modeling can create meaningful business impact.
The Director will also provide strategic support for:
• Customer intelligence and behavioral analytics.
• AI-enabled product and platform capabilities.
• Revenue growth and pricing optimization.
• Marketing performance and personalization strategy.
• Forecasting, demand planning, and operational efficiency.
• Data science governance and responsible AI practices.
• Executive reporting and decision-support frameworks.
• Enterprise experimentation and measurement strategy.
This position requires someone who can move beyond building models and help the business understand how data science changes decisions, improves performance, and creates long-term competitive advantage.
• Primarily remote work environment with occasional leadership meetings, planning sessions, or company events as needed.
• Standard business hours with flexibility required for cross-functional collaboration, executive deadlines, model deployment milestones, or urgent business priorities.
• Occasional travel may be required for leadership off-sites, strategy meetings, team workshops, or enterprise planning sessions.
• Regular interaction with senior executives, product leaders, engineering teams, analytics teams, and business stakeholders.
• Fast-paced, data-rich environment with high visibility and strong expectations for measurable impact.
• Requires the ability to manage multiple strategic initiatives while maintaining strong technical oversight and team leadership.
• Data Science Leadership
• Machine Learning Strategy
• Artificial Intelligence
• Predictive Analytics
• Customer Intelligence
• Personalization
• Experimentation and A/B Testing
• Forecasting and Optimization
• Advanced Analytics
• Data Products
• Model Governance
• Responsible AI
• Executive Decision Support
• Digital Product Analytics
Compensation Package: $250K – $349K
The total compensation package may include base salary, performance-based bonus, long-term incentives, and additional leadership-level benefits depending on experience, qualifications, and final role alignment.
Benefits may include:
• Comprehensive medical, dental, and vision coverage.
• Performance-based bonus eligibility.
• Long-term incentive opportunities.
• Retirement savings plan with company contribution.
• Paid time off and company holidays.
• Remote work flexibility.
• Executive-level visibility and strategic leadership exposure.
• Professional development and leadership growth opportunities.
• Wellness, employee assistance, and work-life support programs.
• Access to modern data, AI, cloud, and analytics platforms.
This is an opportunity to join a large, data-driven organization at a stage where artificial intelligence, machine learning, and advanced analytics are central to the company’s growth strategy.
The Director of Data Science will have the ability to influence major decisions across product, customer experience, marketing, operations, and revenue strategy. This is not a back-office analytics role. It is a strategic leadership position designed for someone who wants to build scalable data science capabilities that directly shape business outcomes.
You will work with large-scale customer, product, operational, and behavioral datasets while leading a team focused on solving real business problems. The role offers strong executive visibility, meaningful ownership, and the opportunity to help define how a major enterprise uses AI and data science to compete, grow, and innovate.
For a data science leader who enjoys building teams, scaling machine learning solutions, advising executives, and turning complex data into measurable business value, this position offers the scope, platform, and influence to make a significant impact.
At Admiral Talent, our vision is to redefine staffing through genuine partnerships, innovation, and a people-first mindset. Guided by experienced leadership, we’re committed to driving growth, empowering talent, and delivering exceptional results for every client we serve.