Job description

Job Description The Opportunity We are looking for a Senior Data Scientist to advance the science behind personalization, recommendations, search, and browse relevance across our digital shopping experience. You will combine deep machine learning expertise with strong experimentation and customer understanding to improve how we match customers with relevant products and experiences. This role will help evolve our Data Science organization from isolated model development toward connected, measurable, and reusable personalization capabilities. Note: This position is offered as a hybrid role in the Seattle, WA area. You must be willing to work in office at the Nordstrom Seattle office for a minimum of 4 days per week to be considered for this position. What You Will Do 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, leveraging existing open-source and pre-trained resources (e.g., Hugging Face) rather than building from scratch, including embeddings, sequence models, multimodal models, foundation models, and generative AI where they provide measurable value. Design offline evaluation frameworks that better predict online customer outcomes. Partner with Product and Engineering to define the customer problem, desired outcome, and success metrics, and determine the appropriate scientific approach. Design and analyze online experiments to understand the impact of new relevance and personalization approaches. Investigate differential effects across customer cohorts, product categories, and shopping contexts. Help connect candidate generation, ranking, customer understanding, product understanding, and feedback signals into a more coherent personalization system. Develop reusable evaluation, feature, and modeling approaches that can be applied across multiple customer experiences. Use AI-assisted development in your daily workflow (e.g., Claude Code) and bring agentic and LLM-based approaches into personalization decisioning, to increase research and experimentation velocity. Mentor scientists and help establish strong technical practices across the team. What Success Looks Like Offline evaluation becomes more predictive of real customer outcomes. Recommendation and relevance capabilities increasingly share common customer and product understanding. The team tests a broader set of hypotheses faster without lowering scientific standards. Personalization capabilities are reused across multiple surfaces rather than developed independently. New ML and GenAI approaches are adopted based on demonstrated customer value rather than novelty. Other scientists improve their technical and experimental practices through your leadership. What We Are Looking For Minimum of 6 years of hands-on experience in Data Science or Machine Learning roles. Bachelor s degree in a quantitative field (e.g., statistics, computer science, mathematics, engineering) or equivalent practical experience; advanced degree preferred. 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 ML techniques, including adapting existing open-source and pre-trained models. Strong Python and SQL skills, including working with large-scale data (e.g., BigQuery). Experience using AI tools (e.g., Claude Code) in your daily workflow and applying LLM or agentic approaches to real problems. Familiarity with cloud ML platforms such as Google Vertex AI or AWS machine learning pipelines is a plus. 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 the right problem and defining outcome metrics with business partners. Strong technical communication and mentorship skills. The Mindset We Value You see the model as one part of a larger customer system. You care about whether the entire system makes better choices for customers, not simply whether an offline metric improves. You adopt new AI techniques when they create measurable value and simplify or scale how the team works. 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. Pay Range Details The pay range(s) below has been provided in compliance with state specific laws. Pay ranges may be different for other locations. Pay offers are dependent on the location, as well as job-related knowledge, skills, and experience. $166,000.00 - $258,000.00 Annual We’ve got you covered… Our employees are our most important asset and that’s reflected in our benefits. Nordstrom is proud to offer a variety of benefits to support employees and their families, including: Medical/Vision, Dental, Retirement and Paid Time Away Life Insurance and Disability Merchandise Discount and EAP Resources This position may be eligible for performance-based incentives/bonuses. Benefits include 401k, medical/vision/dental/life/disability insurance options, PTO accruals, Holidays, and more. Eligibility requirements may apply based on location, job level, classification, and length of employment. Learn more in the Nordstrom Benefits Overview by copying and pasting the following URL into your browser: careers.nordstrom.com A few more important points... The job posting highlights the most critical responsibilities and requirements of the job. It’s not all-inclusive. There may be additional duties, responsibilities and qualifications for this job. 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. Applicants with disabilities who require assistance or accommodation should contact the nearest Nordstrom location, which can be identified at www.nordstrom.com . 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. Current Nordstrom employees: To apply, log into Workday, click the Careers button and then click Find Jobs. Nordstrom keeps job postings open for at least one day after the posting date. © 2026 Nordstrom, Inc

Requirements

Must-haves

Job Description The Opportunity
We are looking for a Senior Data Scientist to advance the science behind personalization, recommendations, search, and browse relevance across our digital shopping experience.
You will combine deep machine learning expertise with strong experimentation and customer understanding to improve how we match customers with relevant products and experiences.
This role will help evolve our Data Science organization from isolated model development toward connected, measurable, and reusable personalization capabilities.
Note: This position is offered as a hybrid role in the Seattle, WA area. You must be willing to work in office at the Nordstrom Seattle office for a minimum of 4 days per week to be considered for this position.
Develop and improve recommendation, ranking, relevance, and personalization approaches.
Build deeper representations of customer intent, product understanding, and shopping context.
Design offline evaluation frameworks that better predict online customer outcomes.
Partner with Product and Engineering to define the customer problem, desired outcome, and success metrics, and determine the appropriate scientific approach.
Design and analyze online experiments to understand the impact of new relevance and personalization approaches.
Investigate differential effects across customer cohorts, product categories, and shopping contexts.
Help connect candidate generation, ranking, customer understanding, product understanding, and feedback signals into a more coherent personalization system.
Develop reusable evaluation, feature, and modeling approaches that can be applied across multiple customer experiences.
Use AI-assisted development in your daily workflow (e.g., Claude Code) and bring agentic and LLM-based approaches into personalization decisioning, to increase research and experimentation velocity.
Mentor scientists and help establish strong technical practices across the team.
What Success Looks Like
Offline evaluation becomes more predictive of real customer outcomes.
Recommendation and relevance capabilities increasingly share common customer and product understanding.
The team tests a broader set of hypotheses faster without lowering scientific standards.
Personalization capabilities are reused across multiple surfaces rather than developed independently.
New ML and GenAI approaches are adopted based on demonstrated customer value rather than novelty.
Other scientists improve their technical and experimental practices through your leadership.

Nice-to-haves

Bachelor s degree in a quantitative field (e.g., statistics, computer science, mathematics, engineering) or equivalent practical experience; advanced degree preferred.
Familiarity with cloud ML platforms such as Google Vertex AI or AWS machine learning pipelines is a plus.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaillmmlpythonsqlaws

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto