Product Data Analyst, Consumer

Role Overview

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We are looking for a Product Data Analyst to join our Consumer team which tackles a complex data environment, building out data assets, running experiments, and many more unstructured analytics tasks to support the core listings business.  

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.

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What you’ll do

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• Using your SQL expertise, conduct exploratory empirical analyses that bridge disparate data sources (e.g. website usage, subscription records, inventory volumes, etc.) to quantify product performance, user behavior, and/or market trends. Doing so will require distilling unstructured “big data” into actionable insights.
• Creatively compress sweeping, high-level exploratory requests into specific calculations that address your stakeholders’ underlying needs.
• Relentlessly dig into the data – consulting with other individuals and teams as you judge necessary – beyond the letter of the initial assignment, to hammer out any anomalies or self-direct your inquiry into other relevant issues.
• Be comfortable escalating and automating your analyses using R/Python scripting.
• Be the authority on A/B experimentation, advising engineers and product managers on everything from the necessary data points to collect, required sample sizes, optimal metrics to examine, robustness of numerical findings, and the bottom-line success or failure of the tested changes.
• Provide technical guidance on and ideas for improving A/B testing-related tools, algorithms, and automated processes.
• Conduct self-directed research on the latest trends in A/B experimentation, and map out internal improvements based on your findings.
• Advocate for specific, data-driven product innovations that help further high-level company strategy, primarily in partnership with the Product/Engineering teams.
• Participate in brainstorming and planning discussions across the organization to these ends.
• Avoid passivity in the face of flawed proposals; tactfully and persuasively push back against potential missteps.
• Craft the metrics that define business success, condensing abstract or loosely-defined concepts down to concrete calculations.
• Audit and improve existing metrics to better inform the business’ needs.
• Build intuitive dashboards and other visual monitoring tools to guide daily decision-making by senior stakeholders and the company at large.
• Experiment with new kinds of visualizations that you believe could be better utilized in the organization.
• 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.

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What you’ll bring

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• 2+ years of experience in an analytics or analytics-adjacent field, ideally involving complex data modeling, quantitative analysis, and applied statistics.
• Expert fluency in SQL. Experience with statistical programming (R, Stata, SAS, Python) is desirable.
• Working understanding of core statistical concepts (regression, significance testing, omitted variable bias, independence/dependence, etc.).
• Knack for creative data visualizations.
• 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.
• Excellent verbal and written communication skills. Very comfortable presenting high-impact and potentially sensitive findings to senior leadership.
• 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, Looker, Jira, Salesforce, Google/MS suite