Data Scientist, Product Analytics

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Company Overview

A growing AI technology organization is developing ambitious AI products designed to operate in demanding, real-world environments. The organization focuses on building high-performance AI systems and relies heavily on rigorous measurement, experimentation, and data-driven product development to ensure its technology delivers reliable results.

The Opportunity

The organization is seeking a Data Scientist, Product Analytics to measure and evaluate how effectively its AI agent fleets identify and resolve software defects. This role will own the analytical foundation behind product performance, including detection precision and recall, remediation success rates, experiment design, and statistical evaluation.

The successful candidate will have strong experience in data science, product analytics, quantitative analysis, or machine learning analysis. The role requires hands-on experience measuring the quality of AI or machine learning systems using data, as well as practical experience using AI tools in analytical workflows.

The ideal candidate will be highly proficient in Python and SQL, capable of distinguishing causation from correlation, and committed to producing accurate and defensible analysis. The role requires someone who values evidence-based conclusions and can translate complex findings into actionable recommendations.

Key Responsibilities

• Define and own metrics that measure how effectively AI agent fleets identify and resolve software defects.
• Measure detection precision and recall against real-world customer codebases.
• Quantify remediation success rates and evaluate the strength of supporting validation evidence.
• Design experiments to determine whether product or model changes produce meaningful improvements.
• Partner with engineering teams on evaluation design to ensure agent runs are measured consistently over time.
• Build reliable and reproducible analysis pipelines using Python and SQL.
• Develop analytical processes that other team members can independently rerun and trust.
• Translate analytical findings into clear recommendations for engineering, product, and leadership teams.
• Own reporting processes that ensure product claims and performance assessments remain grounded in reliable evidence.
• Investigate product performance, identify trends, and provide insights that support data-driven decision-making.

Required Qualifications

• Strong working proficiency in Python and SQL.
• Solid understanding of statistics, experimental design, and statistical inference.
• Experience analyzing complex, messy, real-world datasets and drawing defensible conclusions.
• Ability to transform ambiguous business or product questions into actionable metrics.
• Strong understanding of causality, bias, and confounding factors.
• Excellent written and verbal communication skills.
• Ability to operate effectively in a fast-moving and highly collaborative environment.
• Demonstrated experience producing analysis that influenced or changed a business, product, or engineering decision.
• Hands-on experience measuring the quality or performance of AI or machine learning systems.
• Regular use of AI tools as part of analytical or data science workflows.

Preferred Qualifications

• Experience measuring the quality and performance of machine learning or AI systems.
• Experience with causal inference methodologies or Bayesian analysis.
• Experience working with data warehouses.
• Experience with dbt or similar data transformation and analytics workflows.
• Experience developing notebook-to-production data workflows.
• Familiarity with software testing and quality measurement.
• Understanding of CI pipelines and developer tooling metrics.
• Experience working with product analytics for AI-powered or software development products.

Compensation

• Competitive salary.
• Meaningful equity opportunity.

Disclaimer

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