Senior Data Scientist – AI & ML | MLOps Enablement (Hybrid – Seattle, WA)

Job Summary

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 owns the ML Platform capability, allowing Data Scientists and engineers to 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.

About the Role

This is a hybrid role in Seattle, WA. Candidates must be available to work in the office a minimum of 4 days/week. 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.

Responsibilities

• Run end-to-end POC validation for new platform capabilities such as Feature Store, Endpoints, Model Evaluation, AutoML, BigQuery ML etc., independently, before they reach DS teams at scale.
• Attend DS team planning and design sessions as an embedded practitioner; surface real workflow pain points and translate them into reusable MLOps platform requirements.
• Design and own the Model Evaluation Framework, defining metrics, thresholds, and evaluation pipelines for batch, online, and streaming use cases on Vertex AI.
• Build model-type-aware Feature Store schemas, endpoint configurations, and evaluation pipelines that accommodate the fundamentally different needs of different ML models.
• Lead benchmarking of Nordstrom’s platform against industry standards — SageMaker vs. Vertex AI — across feature parity, cost, and DS practitioner ergonomics.
• Author DS-native documentation, onboarding guides, and quickstart notebooks that lower the adoption barrier for new platform features.
• 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.
• Own model card standards, capturing what actually matters to a practitioner, not just governance checkboxes.
• Communicate complex trade-offs and platform decisions to technical and non-technical stakeholders across DS, engineering, and leadership.

Requirements

• Bachelor’s, Master’s, or PhD in Statistics, Data Science, Computer Science, Engineering, or a related technical field required.
• 10+ years of hands-on Data Science experience with production model delivery across multiple ML (classification, ranking, NLP, time-series, recommendation) and GenAI models.
• Deep expertise in model evaluation — defining metrics, thresholds, and evaluation pipelines for real-world production models.
• Proficiency in Python with experience writing clean, maintainable, production-quality ML code.
• Strong understanding of ML monitoring — data drift, prediction drift, and concept drift detection.
• Experience with experiment tracking and model lifecycle management.
• Ability to translate between DS practice and platform engineering — comfortable driving design decisions, authoring DS-native documentation, and engaging in technical design reviews.
• Self-directed; comfortable owning POC work end-to-end without a dedicated DS team structure.
• Hands-on experience with GCP and Vertex AI — Workbench, Pipelines, Feature Store, Model Endpoints, Model Registry, Model Evaluation (preferred).
• Familiarity with AWS SageMaker for cross-cloud benchmarking and comparison context (preferred).
• Understanding of CI/CD for ML, containerization, and pipeline orchestration — able to engage at platform depth alongside MLOps engineers (preferred).
• Prior experience in ML platform adoption, enablement, or developer experience work (preferred).
• Experience operating within a mature ML lifecycle — versioning, lineage tracking, model governance, staged rollouts, and model deprecation practices at enterprise scale (preferred).
• Exposure to agentic AI patterns, LLM evaluation frameworks, or Vertex AI Agent Builder (preferred).

Qualifications

• Bachelor’s, Master’s, or PhD in Statistics, Data Science, Computer Science, Engineering, or a related technical field required.
• 10+ years of hands-on Data Science experience with production model delivery across multiple ML (classification, ranking, NLP, time-series, recommendation) and GenAI models.
• Deep expertise in model evaluation — defining metrics, thresholds, and evaluation pipelines for real-world production models.
• Proficiency in Python with experience writing clean, maintainable, production-quality ML code.
• Strong understanding of ML monitoring — data drift, prediction drift, and concept drift detection.
• Experience with experiment tracking and model lifecycle management.
• Ability to translate between DS practice and platform engineering — comfortable driving design decisions, authoring DS-native documentation, and engaging in technical design reviews.
• Self-directed; comfortable owning POC work end-to-end without a dedicated DS team structure.
• Hands-on experience with GCP and Vertex AI — Workbench, Pipelines, Feature Store, Model Endpoints, Model Registry, Model Evaluation (preferred).
• Familiarity with AWS SageMaker for cross-cloud benchmarking and comparison context (preferred).
• Understanding of CI/CD for ML, containerization, and pipeline orchestration — able to engage at platform depth alongside MLOps engineers (preferred).
• Prior experience in ML platform adoption, enablement, or developer experience work (preferred).
• Experience operating within a mature ML lifecycle — versioning, lineage tracking, model governance, staged rollouts, and model deprecation practices at enterprise scale (preferred).
• Exposure to agentic AI patterns, LLM evaluation frameworks, or Vertex AI Agent Builder (preferred).

Benefits

Nordstrom offers a variety of benefits to support employees and their families, including:

• Medical/Vision, Dental, Retirement
• Paid Time Away
• Life Insurance and Disability
• Merchandise Discount and EAP Resources

For Los Angeles or San Francisco applicants: Nordstrom conducts background checks after conditional offer and considers 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.