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.