Senior Data Scientist - Personalization & Relevance

Nordstrom • Seattle, WA

12d • Hybrid

About The Position

Nordstrom is seeking a Senior Data Scientist to advance personalization, recommendations, search, and browse relevance across its digital shopping experience. The role combines machine learning expertise, experimentation, and customer understanding to improve how customers are matched with relevant products and experiences. It will help evolve the Data Science organization toward connected, measurable, and reusable personalization capabilities.

This is an applied data science role focused on identifying customer problems, proposing solutions, iterating, and delivering with Engineering. The position is hybrid in the Seattle, Washington area, with a requirement to work in the Nordstrom Seattle office at least four days per week.

The successful candidate will develop recommendation and relevance capabilities, build stronger representations of customer intent and product understanding, and apply modern machine learning and generative AI approaches when they demonstrate measurable value. They will partner with Product and Engineering, design offline and online evaluations, investigate outcomes across customer cohorts and shopping contexts, and create reusable modeling and evaluation approaches. The role also includes mentoring scientists and strengthening team technical practices.

Requirements

• At least 6 years of hands-on experience in Data Science or Machine Learning roles.
• Bachelor’s degree in a quantitative field such as statistics, computer science, mathematics, or engineering, or equivalent practical experience.
• Deep experience with recommendation systems, ranking, personalization, search, or information retrieval.
• Strong knowledge of machine learning, deep learning, experimentation, and statistical evaluation.
• Experience with embeddings, neural ranking, transformers, or related modern machine learning techniques, including adapting existing open-source and pre-trained models.
• Strong Python and SQL skills, including experience working with large-scale data such as BigQuery.
• Experience using AI tools in daily workflows and applying LLM or agentic approaches to real problems.
• Experience moving models from research through production evaluation.
• Ability to reason about customer and business outcomes beyond offline model metrics.
• Experience working closely with Product and Engineering, including framing problems and defining outcome metrics with business partners.
• Strong technical communication and mentorship skills.
• Willingness to work in the Nordstrom Seattle office at least 4 days per week.

Nice To Haves

• Advanced degree.
• Familiarity with cloud ML platforms such as Google Vertex AI or AWS machine learning pipelines.

Responsibilities

• Develop and improve recommendation, ranking, relevance, and personalization approaches.
• Build deeper representations of customer intent, product understanding, and shopping context.
• Evaluate and apply modern approaches, including embeddings, sequence models, multimodal models, foundation models, and generative AI, leveraging open-source and pre-trained resources where appropriate.
• Design offline evaluation frameworks that better predict online customer outcomes.
• Partner with Product and Engineering to define customer problems, desired outcomes, success metrics, and appropriate scientific approaches.
• Design and analyze online experiments to assess the impact of relevance and personalization approaches.
• Investigate differential effects across customer cohorts, product categories, and shopping contexts.
• Connect candidate generation, ranking, customer understanding, product understanding, and feedback signals into a more coherent personalization system.
• Develop reusable evaluation, feature, and modeling approaches for multiple customer experiences.
• Use AI-assisted development tools in daily work and apply agentic and LLM-based approaches to personalization decisioning.
• Mentor scientists and help establish strong technical practices across the team.
• Move models from research through production evaluation and assess them against customer and business outcomes.

Benefits

• Medical, vision, and dental coverage.
• Retirement benefits, including a 401(k).
• Paid time away and PTO accruals.
• Life insurance and disability insurance options.
• Merchandise discount.
• Employee Assistance Program (EAP) resources.
• Holidays.
• Potential eligibility for performance-based incentives or bonuses.

What This Job Offers

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