Data Scientist, Product

This role is based in New York, NY.

Compensation:

$147,000/year to $208,000/year + bonus + equity + benefits

Responsibilities:

• Design and evaluate A/B experiments to measure the causal impact of product changes on user behavior and key product metrics.
• Develop and maintain predictive models and statistical frameworks to generate actionable insights that inform product strategy.
• Build scalable data pipelines and self-service visualization interfaces that enable cross-functional partners to explore and interpret product performance data.
• Define success metrics and measurement frameworks that connect product goals to business outcomes.
• Conduct exploratory and confirmatory analyses on large-scale behavioral datasets to identify opportunities and surface risks.
• Collaborate with product managers, engineers, and designers to translate analytical findings into prioritized product decisions.
• Communicate complex analytical results clearly to technical and non-technical stakeholders through written narratives and data presentations.
• Advise cross-functional partners on analytical design, hypothesis formulation, and interpretation of quantitative and qualitative research.
• Integrate AI tools into analytical workflows to accelerate insight generation, improve reproducibility, and expand the scope of analyses.
• Contribute to team-level goal setting by sizing opportunities, tracking operational performance, and identifying gaps in existing measurement approaches.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Experience in data science, applied analytics, or a related quantitative field working on consumer or enterprise products.
• Experience designing and analyzing controlled experiments, including hypothesis formulation, statistical testing, and interpretation of results.
• Experience writing production-quality code in SQL and at least one scripting language such as Python or R to manipulate and analyze large-scale datasets.
• Experience building predictive models using statistical or machine learning techniques and translating model outputs into product recommendations.
• Experience developing data visualizations and self-service dashboards to communicate product performance to diverse stakeholders.

Preferred Qualifications:

• Experience building forecasting models using time series methods to project product or business metrics.
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews).
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies.
• Experience working on social platforms, feed ranking, notifications, or engagement products where behavioral data is high-volume and high-dimensional.
• Experience applying causal inference methods such as difference-in-differences, instrumental variables, or regression discontinuity in a product analytics context.
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements).
• Demonstrated ability to influence product roadmap decisions through data storytelling and stakeholder alignment at the team or organizational level.