Senior Manager, Data Science

Nordstrom • Seattle, WA

4d • Hybrid

About The Position

Nordstrom is seeking a Senior Manager of Data Science to lead and develop a team of data scientists and ML operations engineers working to improve product discovery and shopping across digital experiences. The team’s work spans personalization, recommendations, search and browse relevance, customer and product understanding, experimentation, and measurement. The leader will guide the organization beyond primarily building and evaluating models toward identifying customer problems, choosing effective interventions, measuring value, and scaling successful approaches into reusable capabilities.

This leader will establish strategy and operating practices for data science across digital product discovery, partner with Product, Engineering, UX, and business leaders, and build a rigorous approach to experimentation and measurement. The role includes developing team capabilities in areas such as causal reasoning, optimization, personalization, recommendation systems, ranking, and customer understanding; reducing repetitive work through standardized and reusable tools; and applying GenAI and emerging AI capabilities to accelerate learning and support customer and internal capabilities.

The Senior Manager will build, coach, and develop a high-performing team, strengthen its scientific rigor and business judgment, and help establish scalable systems and platforms with Engineering. The position is hybrid in the Seattle, Washington area and requires working from Nordstrom’s Seattle office at least four days per week.

Requirements

• 10+ years of hands-on experience in Data Science or Machine Learning roles.
• 3+ years managing Data Science, Applied Science, or Machine Learning teams working on customer-facing products.
• Bachelor's degree in a quantitative field such as statistics, computer science, mathematics, or engineering, or equivalent practical experience.
• Deep experience in at least one of personalization, recommendation systems, search/ranking, customer modeling, marketplace optimization, or digital commerce.
• Strong knowledge of experimentation, statistical measurement, and causal inference.
• Demonstrated ability to connect scientific work to product and business decisions.
• Experience moving teams from bespoke model development toward reusable platforms, frameworks, or scalable capabilities.
• Experience applying modern machine learning and GenAI techniques to real customer or business problems, including daily use of AI tools and agentic or LLM-based approaches in decisioning.
• Hands-on comfort with Python, SQL, and large-scale data such as BigQuery, sufficient to read, review, and guide the team's code and outputs.
• Strong product and business judgment, including the ability to distinguish technically interesting work from work that materially improves customer outcomes.
• Proven ability to lead organizational change, establish new standards, and raise the performance bar of an existing team.
• Strong people leadership, including hiring, coaching, performance management, succession development, and creating strong technical leadership.
• Ability to communicate complex scientific ideas clearly and influence senior Product, Engineering, and business leaders.
• Willingness to work in the Nordstrom Seattle office at least four days per week.

Nice To Haves

• An advanced degree.
• Familiarity with open-source AI resources such as Hugging Face and OpenRouter.
• Familiarity with cloud ML platforms such as Google Vertex AI and AWS.

Responsibilities

• Set data science strategy for personalization, recommendations, search, browse, and digital product discovery.
• Partner with Product, Engineering, UX, and business leaders to identify high-value customer problems before selecting technical solutions.
• Establish hypotheses, success measures, targets, guardrails, and decision criteria before significant experimentation.
• Build an experimentation and measurement discipline connecting model performance to customer behavior, conversion, revenue, long-term engagement, and other meaningful outcomes.
• Develop team capabilities in experimentation, causal reasoning, optimization, personalization, recommendation systems, ranking, and customer understanding.
• Identify repetitive data science work to standardize, automate, or turn into reusable capabilities.
• Apply GenAI and emerging AI capabilities to accelerate research, experimentation, evaluation, and learning.
• Champion AI-native ways of working, including agentic architectures and LLMs in decisioning where useful.
• Partner with Engineering to create scalable systems and platforms that enable successful scientific approaches to be reused broadly.
• Build, coach, and develop a high-performing team of data scientists and ML operations engineers.
• Foster an environment in which scientists challenge assumptions, frame problems clearly, and recommend actions.
• Establish an operating model for problem framing, success definition, experimentation, and recommendations.
• Increase team capacity devoted to customer understanding, problem definition, experimentation strategy, and decision-making.
• Improve the connection between offline model metrics, online experiments, customer outcomes, and business results.
• Develop a roadmap for how GenAI will change team workflows and the capabilities provided to customers and internal partners.
• Strengthen the team's technical and leadership talent.

Benefits

• Medical, vision, and dental benefits.
• Retirement benefits.
• Paid time away, PTO accruals, and holidays.
• Life insurance and disability insurance options.
• Merchandise discount.
• Employee Assistance Program (EAP) resources.
• May be eligible for performance-based incentives or bonuses.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior