Senior Data Analyst: Customer Feedback & NLP Insights

Jobtailor

Seattle (WA)

On-site

USD 120,000 - 160,000

Full time

14 days+

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Job summary

Jobtailor is seeking a Senior Data Analytics professional to lead customer feedback analysis in Seattle. You will apply SQL, Python/R and NLP techniques to classify comments, measure sentiment, and identify trends.

You will own the feedback taxonomy and survey text analytics, delivering end-to-end analyses and strategic recommendations to senior leaders. You will collaborate with cross-functional teams, mentor junior analysts, and continuously evolve models and data sources to improve insights

Qualifications

Bachelor’s degree or equivalent experience in analytics or related field.
5+ years of data analytics experience, including complex/ambiguous work.
Strong SQL skills; hands-on BigQuery or similar cloud data environment.
Python/R experience for analysis, testing methods, or automation.
Experience with unstructured text analysis using NLP/LLMs/classification methods.
Ability to validate results, understand limitations, and select appropriate statistics.
Ability to translate data into concise insights and strategic recommendations for senior leaders.
Experience building support for analytics priorities and influencing cross-team decisions.
Ability to engage stakeholders, assess data access/effort, and align on approach.
Experience with version-control tools (GitHub/GitLab) and data viz tools (Looker/Tableau).
Demonstrated initiative, independent judgment, and ability to manage priorities.
Experience with AI-assisted coding tools (Claude Code) is a plus.
Experience analyzing sentiment or unstructured feedback and connecting feedback to behavioral data.

Responsibilities

Develop, test, and improve methods for classifying customer comments and measuring sentiment using LLMs and other text analytics tools.
Establish validation standards through peer review, samples, and benchmarks.
Own and evolve models, workflows, and data sources; design next iteration independently.
Use SQL, Python/R, and BigQuery to build repeatable datasets and tools for self-serve exploration.
Own customer-feedback taxonomy and survey text analytics, including definitions and releases.
Deliver end-to-end analysis from business question to recommendations and storytelling.
Produce recurring and event-based analyses, including emerging trends.
Partner with stakeholders to define success, scope data access, and align on approaches.
Build business cases and gain leadership support for analytics priorities and roadmap.
Collaborate with Business, Technology, Product, and Analytics teams to deliver value.
Mentor junior analysts on analytics, storytelling, and responsible AI use.
Collaborate with analysts through code reviews and shared standards.