Senior Data Insights Analyst, Mobile App

NPR is a mission-driven multimedia organization producing news, information, and music programming in partnership with independent public radio stations. The Senior Data Insights Analyst, Mobile App will own mobile product analytics and experimentation for the NPR App, using advanced SQL and raw event data to generate insights, design A/B tests, and guide product strategy. The role also provides technical mentorship, develops self-service tools, and establishes data quality and reporting standards.

Responsibilities:

• Write, optimize, and QC complex SQL queries using BigQuery; transform raw event logs, access nested arrays, and perform advanced cohort, pattern, and behavioral analysis across app and web platforms
• Lead the experimentation lifecycle on NPR’s owned and operated platforms using Optimizely (or comparable tools); partner across teams to formulate hypotheses, design rigorous A/B testing frameworks, run experiments, and translate results into product recommendations
• Deliver foundational trend reporting and deep-dive mobile app analytics to product managers, newsroom leaders, and station stakeholders to advocate for audience needs and guide strategy
• Share advanced SQL and analytical expertise with teammates; build sustainable self-service insight tools and train cross-functional partners to utilize data effectively in daily decision-making
• Streamline scheduled queries, data summaries, and automated pipelines; partner with Data Products to diagnose and resolve tracking anomalies and optimize tool design based on user needs
• Manage incoming analytical requests by evaluating business impact, aligning deliverables directly with departmental strategy and media landscape trends
• Proactively share research tools and insights to cultivate a transparent, data-driven learning culture across NPR and partner stations nationwide
• Establish guidelines, data dictionaries, and technical documentation for app, video, and web metrics to ensure organizational reporting consistency

Requirements:

• 5+ years of advanced SQL experience: Demonstrated expertise writing complex SQL queries from scratch, querying raw, unaggregated event logs, and utilizing data warehousing environments (e.g., BigQuery, Dataform)
• Raw Data & Array Manipulation Expertise: Proven ability to fetch, transform, and manipulate complex data structures, taking raw data to create audience cohorts and behavioral pattern modeling
• 5+ years of Mobile & Web Analytics: Hands-on experience with app and digital behavioral analytics datasets (e.g., Google Firebase, GA4) across mobile product environments
• 2+ years of Experimentation Design: Demonstrated experience formulating, executing, and evaluating A/B and multivariate tests using enterprise platforms (e.g., Optimizely)
• Data Visualization & Reporting: Expert proficiency in converting complex SQL outputs into clear visual stories (Looker, Tableau) and advanced spreadsheet models (Excel/Google Sheets) for non-technical stakeholders
• Stakeholder Enablement & Training: Proven track record of training partners on data tools, establishing self-service frameworks, and mentoring peers on SQL and data hygiene best practices
• Exceptional ability to write efficient SQL to unnest arrays, parse JSON/struct fields, and build scalable datasets from raw event-level digital behavior
• Deep competency in A/B testing design, statistical significance testing, hypothesis formulation, and post-test behavioral analysis
• Mastery in presenting quantitative findings to executive, technical, and non-technical audiences with clarity and actionable strategic connections
• Demonstrated dedication to elevating team-wide technical capabilities through SQL code reviews, documentation, and training
• Strong ability to independently navigate shifting priorities, evaluate business impact, and lead complex projects from inception to completion
• Experience within digital news media, public broadcasting, or media streaming platforms
• Statistical modeling proficiency using scripting languages such as R or Python
• Demonstrated success in building cross-functional partnerships to solve complex, multi-departmental analytical problems