
Leading company in the retail industry
Senior Data Scientist – AI & ML | MLOps Enablement (Hybrid – Seattle, WA) at Nordstrom
About the role
Job Description
The Developer Platform Organization’s mission is to accelerate the delivery of reliable and secure platforms that make developers feel good and code their best. Developer Platform exists to help engineers focus on business challenges and minimize their work on infrastructure and operations — developing and supporting platforms and tools for the entire Software Development Lifecycle. Centralized platform tooling allows developer tooling to be written once, and not repeated for each team or project.
Within Developer Platform, the MLOps Enablement team owns the ML Platform capability. Data Scientists and engineers can build, deploy, and operate machine learning models on managed, standards-compliant infrastructure — without standing up their own model serving or ML pipeline tooling. We deliver a unified, secure, and cost-efficient platform built on Vertex AI.
We are looking for a Senior Data Scientist to join the MLOps Enablement team as an embedded DS practitioner. This is not a traditional Data Science role focused on owning models — it is a platform-facing role for a DS practitioner who wants to shape the infrastructure and tooling that Data Scientists across Nordstrom depend on every day. You will be the DS voice on a platform engineering team, ensuring our capabilities are designed for how Data Scientists actually work — so adoption is fast, intuitive, and does not require a custom engagement every time.
This role is offered as hybrid in Seattle, WA. Candidates must be available to work in office at the Nordstrom corporate headquarters a minimum of 4 days/week to be considered for this position.A day in the life…
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Run end-to-end POC validation for new platform capabilities — Feature Store, Endpoints, Model Evaluation, AutoML, Big Query ML etc. — independently, before they reach DS teams at scale
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Attend DS team planning and design sessions as an embedded practitioner; surface real workflow pain points and translate them into reusable MLOps platform requirements
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Design and own the Model Evaluation Framework — defining metrics, thresholds, and evaluation pipelines for batch, online, and streaming use cases on Vertex AI
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Build model-type-aware Feature Store schemas, endpoint configurations, and evaluation pipelines that accommodate the fundamentally different needs of different ML models
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Lead benchmarking of Nordstrom’s platform against industry standards — Sage Maker vs. Vertex AI — across feature parity, cost, and DS practitioner ergonomics
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Author DS-native documentation, onboarding guides, and quickstart notebooks that lower the adoption barrier for new platform features
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Contribute DS domain expertise to the emerging Vertex AI Agentic Platform — identifying DS workflow pain points as agent use cases and defining evaluation frameworks for agentic responses
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Own model card standards — capturing what actually matters to a practitioner, not just governance checkboxes
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Communicate complex trade-offs and platform decisions to technical and non-technical stakeholders across DS, engineering, and leadership
You own this if you have…
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Bachelor’s, Master’s, or PhD in Statistics, Data Science, Computer Science, Engineering, or a related technical field required
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10+ years of hands-on Data Science experience with production model delivery across multiple ML (classification, ranking, NLP, time-series, recommendation) and GenAI models
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Deep expertise in model evaluation — defining metrics, thresholds, and evaluation pipelines for real-world production models
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Experience with Feature Store design, feature engineering, and understanding of feature freshness, reuse, and drift across different model families
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Proficiency in Python with experience writing clean, maintainable, production-quality ML code
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Strong understanding of ML monitoring — data drift, prediction drift, and concept drift detection
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Experience with experiment tracking and model lifecycle management
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Ability to translate between DS practice and platform engineering — comfortable driving design decisions, authoring DS-native documentation, and engaging in technical design reviews
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Self-directed; comfortable owning POC work end-to-end without a dedicated DS team structure
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Hands-on experience with GCP and Vertex AI — Workbench, Pipelines, Feature Store, Model Endpoints, Model Registry, Model Evaluation (preferred)
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Familiarity with AWS Sage Maker for cross-cloud benchmarking and comparison context (preferred)
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Understanding of CI/CD for ML, containerization, and pipeline orchestration — able to engage at platform depth alongside MLOps engineers (preferred)
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Prior experience in ML platform adoption, enablement, or developer experience work (preferred)
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Experience operating within a mature ML lifecycle — versioning, lineage tracking, model governance, staged rollouts, and model deprecation practices at enterprise scale (preferred)
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Exposure to agentic AI patterns, LLM evaluation frameworks, or Vertex AI Agent Builder (preferred)
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:
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Medical/Vision, Dental, Retirement and Paid Time Away
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Life Insurance and Disability
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Merchandise Discount and EAP Resources
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.
© 2022 Nordstrom, Inc
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.
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
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: https://careers.nordstrom.com/pdfs/Ben_Overview_17-19.pdf
Required skills
Data science
Machine learning
MLOps
Platform collaboration
Workflow design
Model deployment concepts
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About Nordstrom

Nordstrom
PublicNordstrom, Inc. is an American upmarket department store chain headquartered in Seattle, Washington, and founded by John W. Nordstrom and Carl F. Wallin in 1901. The original store operated exclusively as a shoe store, and a second location opened in 1923.
10,001+
Employees
Seattle
Headquarters
$4.3B
Valuation
Reviews
5 reviews
3.1
5 reviews
Work-life balance
3.0
Compensation
3.5
Culture
2.8
Career
2.5
Management
2.2
45%
Recommend to a friend
Pros
Good training and learning opportunities
Positive customer interaction and helping customers
Decent compensation with commissions
Cons
Management and leadership issues
Poor communication during critical situations
Limited career advancement opportunities
Salary Ranges
44 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · DATA ANALYST 2
1 reports
$138,000
total per year
Base
$120,000
Stock
-
Bonus
-
$138,000
$138,000
Interview experience
4 interviews
Difficulty
2.5
/ 5
Duration
21-35 weeks
Offer rate
25%
Experience
Positive 25%
Neutral 75%
Negative 0%
Interview process
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
Panel Interview
5
Offer
Common questions
Behavioral/STAR
Past Experience
Culture Fit
Technical Knowledge
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