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About the Role
Lead and evolve a team of data scientists and ML operations engineers responsible for improving how customers discover and shop for products across digital experiences. The team works across personalization, recommendations, search and browse relevance, customer and product understanding, experimentation, and measurement. This leader will help evolve the Data Science organization toward a broader mission: understanding customer problems, identifying the right interventions, measuring value creation, and turning successful approaches into reusable capabilities that improve the shopping experience at scale.
Responsibilities
- Set the 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 deciding on a technical solution.
- Establish clear hypotheses, success measures, targets, guardrails, and decision criteria before significant experimentation begins.
- Move the team beyond asking only “Did model B outperform model A?” toward understanding why customer behavior changed, who benefited, and whether the change created meaningful customer and business value.
- Build a strong experimentation and measurement discipline that connects model performance to customer behavior, conversion, revenue, long-term engagement, and other meaningful outcomes.
- Develop the team's capabilities in experimentation, causal reasoning, optimization, personalization, recommendation systems, ranking, and customer understanding.
- Identify repetitive data science work that should be standardized, automated, or turned into reusable capabilities.
- Use GenAI and emerging AI capabilities to increase the speed of research, experimentation, evaluation, and learning.
- Champion AI-native ways of working across the team, including agentic architectures and LLMs in decisioning where they add value.
- Partner with Engineering to create scalable systems and platforms that allow successful scientific approaches to be reused broadly.
- Build, coach, and develop a high-performing team of data scientists and ML operations engineers, raising expectations for scientific rigor, customer understanding, business judgment, and technical excellence.
- Create an environment where scientists are expected to challenge assumptions, frame problems clearly, and recommend actions rather than simply report results.
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.
- Deep experience in at least one of the following: 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 (e.g., Claude Code) and agentic or LLM-based approaches in decisioning.
- Hands-on comfort with Python and SQL and working with large-scale data (e.g., BigQuery), enough to read, review, and guide the team's code and outputs.
- Strong product and business judgment; able 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 within the organization.
- Ability to communicate complex scientific ideas in clear language and influence senior Product, Engineering, and business leaders.
- You believe the job of Data Science is not simply to build models. This is an applied data science role, not a research or reporting function: you identify the problem, propose a solution, iterate quickly, and deliver with Engineering.
- You start with the customer and the decision that needs to be made. You use science to reduce uncertainty, test assumptions, understand what actually works, and help the organization make better decisions.
- You see AI as an opportunity to eliminate repetitive work, increase the speed of learning, and expand what a small team can accomplish.
- You measure the success of a Data Science organization by the quality of the decisions and customer outcomes it enables, not by the number of models it produces.
- Applicants with criminal histories will be considered in a manner consistent with legal requirements per Los Angeles, Cal. Muni. Code 189.04 and the San Francisco Fair Chance Ordinance.
- Applicants with disabilities who require assistance or accommodation should contact the nearest Nordstrom location.
Skills
- Personalization
- Recommendation systems
- Search/ranking
- Customer modeling
- Marketplace optimization
- Digital commerce
- Experimentation
- Statistical measurement
- Causal inference
- Machine learning
- GenAI
- Python
- SQL
- BigQuery
- Hugging Face
- OpenRouter
- Google Vertex AI
- AWS
Location
- Seattle, WA
Work Type
- Hybrid
Experience Level
- Senior Manager
- 10+ years of experience
- 3+ years of management experience
Education Level
- Bachelor's degree in a quantitative field (e.g., statistics, computer science, mathematics, engineering) or equivalent practical experience
- Advanced degree preferred
Salary/Compensations
- $191,000.00 - $297,000.00 Annual
Benefits
- Medical/Vision
- Dental
- Retirement
- Paid Time Away
- Life Insurance
- Disability
- Merchandise Discount
- EAP Resources
- Performance-based incentives/bonuses
- 401k
About the Company
- Nordstrom is proud to offer a variety of benefits to support employees and their families.
Equal Opportunity
- For Los Angeles or San Francisco applicants: Nordstrom is required to inform you that we conduct background checks after conditional offer and consider qualified applicants with criminal histories in a manner consistent with legal requirements per Los Angeles, Cal. Muni. Code 189.04 and the San Francisco Fair Chance Ordinance.
- For additional state and location specific notices, please refer to the Legal Notices document within the FAQ section of the Nordstrom Careers site.
- Please be mindful that there may be legal notices and requirements related to this job posting that are specific to your state. Review the Career Site FAQ’s for relevant information and guidelines.