Senior Product Data Analyst, Dealer

Role overview

We are looking for a Senior Product Data Analyst to join our Dealer team which tackles a complex data environment, building out core assets, running experiments, and many more unstructured analytics tasks to support the growth of the dealer product suite.

Our Product Data Analytics org as a whole supports our Product and Engineering teams, providing the final word on all analytics for CarGurus’ user and dealer experiences. We are looking for thoughtful, curious, internally driven candidates who can dive into complex data and draw novel, insightful conclusions.

What you’ll do

• Conduct exploratory empirical analyses using SQL and Python that bridge disparate data sources (e.g. website usage, subscription records, inventory volumes, etc.). to quantify product performance, user behavior, and/or market trends. Distill unstructured “big data” around product performance, user behavior and/or market insights into actionable outcomes.
• Creatively compress sweeping, high-level exploratory requests into specific calculations that address your stakeholders’ underlying needs. Relentlessly dig into the data, taking initiative to consult with other individuals and teams as you judge necessary. Go beyond the letter of the initial assignment, to hammer out any anomalies or self-direct your inquiry into other relevant issues.
• Advocate and participate in brainstorming/planning sessions for specific, data-driven product innovations that help further high-level company strategy, primarily in partnership with the Product/Engineering teams.
• Avoid passivity in the face of flawed proposals; tactfully and persuasively push back against potential missteps.
• Craft, audit and improve metrics that define business success, condensing abstract or loosely-defined concepts down to concrete calculations.
• Experiment with new kinds of visualizations, build intuitive dashboards and other visual monitoring tools to guide daily decision-making by senior stakeholders and the company at large. Re-work underlying code to appropriately structure visualization inputs.
• Communicate and present complex quantitative findings in easily digestible terms to company leadership, homing in on key takeaways. Concretely and informatively respond to any probing, on-the-spot follow-up questions from senior decision-makers.
• Conceive of new data assets and build automated transformations (via DBT, LookML, etc.) to bring them to fruition.
• Partner with Data Engineering teams to advance core data modeling/architecture (e.g. user clickstream logging), by optimizing, integrating, and distilling large raw datasets and metadata.
• Draw upon prior experience with expansive, unrefined datasets to fix modeling bottlenecks in quick, scalable, outside-of-the-box ways.
• Use Claude Code and agentic workflows to automate, accelerate, and escalate the sophistication of your analyses.
• Be comfortable escalating and automating your analyses using R/Python scripting.

What you’ll bring

• 4+ years of experience in analytics, ideally involving complex modeling, quantitative analysis and applied statistics 2+ years of experience communicating the high-impact results of analyses to leadership teams to influence strategy
• Hands-on experience leveraging GenAI  to optimize workflows and agentic coding platforms like Claude Code (preferred) or Cursor
• Expert fluency in SQL. A strong background with either R or Python is highly desirable.
• Second-nature understanding of core statistical concepts (regression, significance testing, omitted variable bias, independence/dependence, etc.)
• Willingness to step outside your role and independently come up with novel ideas for the business.
• Willingness to challenge others’ ideas and advocate for your own.
• Strong project planning skills, with experience building roadmaps, estimating required resources, and flagging inter-dependencies with other teams/projects.
• Preferred tools/programs: Snowflake, Snowplow, dbt, Claude Code or Cursor, Looker/Omni, Jira, Salesforce, Google/MS suite