Data Analyst IV

Job Responsibilities:

Produce recurring and ad-hoc customer insight reports for our products that cover each stage of the customer journey, from purchase and delivery through support, warranty, returns, reviews, and social Identify emerging and fast-growing customer issues, size them, and flag likely root causes to the owning team. Run deep dives on customer or product issues for cross-functional partners, applying strong analytical rigor and understanding of the data. Deliver customer insight readouts during product launches, software releases, and war rooms. Use AI agents and LLM tools as the primary way of working, from writing queries to classifying customer text and drafting narratives. Build and document reusable AI workflows for recurring analysis. Review AI-generated analysis before it's shared, checking numbers, classifications, and claims against source data. Set up and maintain quality checks for AI workflows. Build and maintain dashboards and reusable queries for customer experience metrics across the portfolio. Help uphold data integrity by finding and reporting data quality issues, and working with data owners to get them fixed. Track which insights led to product or process changes, and report that impact back to the CX team. Skills:

7+ years of experience in data analytics, customer insights, or CX analytics. 2+ years in customer experience or customer insights analytics. Proficiency writing SQL to query, join, and aggregate large datasets. Experience analyzing customer feedback (support tickets, reviews, surveys, social media). Hands-on experience using LLM tools or AI agents in day-to-day analysis. Experience validating analytical output and checking AI-generated results against source data. Experience turning analysis into recommendations/presentations for non-technical audiences. Experience building multi-step AI workflows or agents (prompt chains, retrieval over docs). Experience evaluating LLM output quality (labeled test sets, precision/recall). Experience with Python/R, consumer electronics/hardware, or CX platforms (Medallia, Qualtrics, etc.). Education/Experience:

Bachelor's degree in analytics, data science, statistics, business, economics, information systems, or a related field, or equivalent practical experience. 7+ years of experience in data analytics, customer insights, CX analytics, or a similar analytical role. 2+ years in customer experience or customer insights analytics. Experience writing SQL to query, join, and aggregate large datasets. Experience analyzing customer feedback such as support tickets, product reviews, surveys, or social media. Hands-on experience using LLM tools or AI agents in day-to-day analysis work, such as data extraction, text classification, summarization, query writing, or report drafting. Experience validating analytical output, including checking AI-generated results against source data and correcting errors. Experience turning analysis into written recommendations and presentations for non-technical audiences. Experience handling multiple requests from different stakeholders with competing deadlines. Experience building multi-step AI workflows or agents for analysis, such as prompt chains, agent skills, or retrieval over documents and data. Experience evaluating LLM output quality, for example with labeled test sets, precision and recall measurement, or structured sampling. Experience with semantic models, metric definitions, or knowledge bases that ground AI tools in business data. Experience with Python or R for data analysis. Experience with consumer electronics or hardware products, especially e-commerce, fulfillment, support, warranty, returns, or quality data. Experience analyzing customer feedback for software or apps alongside hardware. Experience with CX and support platforms such as Medallia, Qualtrics, Salesforce Service Cloud, Brandwatch, or Enterpret. Experience supporting product launches or incident response with fast-turnaround reporting. Experience presenting findings to product, engineering, or operations leaders. Familiarity with smart glasses, VR/AR headsets, or gaming hardware.