Data Analyst 3, Customer Feedback Analytics (Hybrid, Seattle)

Nordstrom•Seattle, WA

11d•Hybrid

About The Position

The CX Measurement team transforms customer feedback into actionable insight through enterprise survey programs, measurement frameworks, and advanced analytics. We are looking for a Data Analyst 3 who will specialize in analyzing unstructured customer feedback to uncover the “why” behind customer experiences — what drives satisfaction, where friction occurs, and where opportunities exist across Nordstrom and Nordstrom Rack. The ideal candidate combines strong technical skills with curiosity, independent judgment, and a passion for storytelling with data. This hands-on role will own and improve CX Measurement's text analytics approach, translate complex findings into clear and trusted customer insights, and help shape how Nordstrom analyzes and uses customer feedback to inform business decisions. LLMs and other AI tools are part of the analytical toolkit; the core of the role is customer insight, analytical rigor, and business impact.

Requirements

Bachelor’s degree in Analytics, Data Science, Statistics, Mathematics, Computer Science, Consumer Insights, or related field, or equivalent experience.
5+ years of experience in data analytics, customer analytics, or a related field, including independently managing complex or ambiguous analytical work.
Strong SQL skills and hands-on experience with BigQuery or a similar cloud-data environment.
Experience using Python/R to conduct analysis, test methods, or automate repeatable work.
Experience analyzing unstructured text using natural language processing, LLMs, classification methods, or other text analytics tools.
Strong analytical judgment, including the ability to validate results, understand limitations, and select appropriate statistical methods for the business question.
Proven ability to translate complex text, behavioral, and operational data into concise insights and strategic recommendations, present them credibly to senior leaders, and gain alignment around action.
Experience building support for analytical priorities, investments, or roadmaps and influencing decisions across multiple teams.
Ability to engage cross-functional stakeholders, uncover business needs, assess data access and effort, and align partners around a shared approach.
Experience with version-control tools such as GitHub or GitLab and data visualization or reporting tools such as Looker or Tableau.
Demonstrated initiative and independent judgment, with the ability to bring a clear point of view, remain open to different approaches, manage competing priorities, and influence cross-functional partners.

Nice To Haves

Experience using AI-assisted coding tools such as Claude Code to support analytical development and workflow automation is a plus.
Experience analyzing sentiment or other unstructured feedback, with an understanding of how source, voice, tone, and context affect interpretation; experience with customer-feedback platforms or connecting feedback with behavioral data preferred.

Responsibilities

Develop, test, and improve methods for classifying customer comments, measuring sentiment, and identifying emerging issues and root causes, using LLMs and other text analytics tools where appropriate.
Establish validation standards through peer review, human-reviewed samples, and benchmarks.
Own and evolve current models, workflows, and data sources; challenge assumptions, evaluate new methods and tools, and independently design the next iteration.
Use SQL, Python/R, and BigQuery to build repeatable datasets and tools that support scalable analysis and self-service exploration.
Own the customer-feedback taxonomy and Medallia survey text analytics, including topic definitions, classification rules, sentiment, releases, and documentation.
Deliver end-to-end analysis, from defining the business question through recommendations and storytelling, connecting customer feedback with behavioral and operational measures such as engagement, trips, spend, and future behavior.
Produce recurring, seasonal, event-based, and rapid-turn customer analysis, including emerging trends.
Partner with stakeholders to uncover needs, define success, scope data access and effort, and align on measurement approaches and priorities.
Build clear business cases and gain leadership support for analytical priorities, investments, and roadmap recommendations.
Collaborate with business, Technology, Product, and Analytics teams to deliver solutions that increase the value and use of customer feedback.
Collaborate with other analysts through code review and shared standards; mentor junior analysts on analytics, storytelling, and responsible use of LLM and AI tools