Data Scientist: Measurement and Decision Sciences

About the role:

Lead experimentation and measurement initiatives

• Design, execute, and analyze A/B tests, holdouts, geo-experiments, and quasi-experimental studies.
• Conduct power analyses, sample sizing assessments, and experiment health reviews.
• Partner with stakeholders to define success metrics, guardrails, and decision criteria.
• Communicate experiment results and recommendations to business leaders.
• Develop measurement plans that enable rigorous evaluation of business initiatives and strategic investments.

Drive decision support and strategic analytics

• Perform deep-dive analyses to identify drivers of acquisition, conversion, retention, customer value, and business performance.
• Evaluate business opportunities using statistical and econometric methods to create customer segmentations.
• Apply causal inference and econometric techniques such as difference-in-differences, synthetic controls, panel data methods, instrumental variables, regression discontinuity, propensity score methods, and time-series analysis to estimate business impact.
• Develop frameworks for measuring incrementality, marketing effectiveness, customer behavior, and long-term business outcomes.
• Build decision-support models and scenario analyses to evaluate strategic alternatives and business tradeoffs.
• Translate ambiguous business problems into structured analytical approaches and actionable recommendations.

Define and operationalize business metrics

• Establish KPI definitions, measurement standards, and analytical best practices.
• Partner with engineering and analytics teams to improve data quality, telemetry, and reporting foundations.
• Ensure consistency of reporting and metric interpretation across business functions.
• Improve measurement frameworks that enable accurate tracking of business performance.

Partner cross-functionally

• Collaborate closely with Marketing, Product, Finance, Operations, and other business stakeholders.
• Influence roadmap prioritization, investment decisions, and strategic planning through analytical evidence.
• Present findings and recommendations to senior stakeholders in a clear and compelling manner.
• Act as a trusted advisor on measurement, experimentation, and business performance questions.

About you:

• 3-5 years of experience in analytics, statistics, econometrics, data science or relevant advanced quantitative degree
• Hands-on experience designing and analyzing experiments and observational studies. 
• Experience applying econometric and causal inference methods to real-world business problems. 
• Strong communication skills with both technical and non-technical audiences.

• Bonus Program
• 401k Retirement
• Medical, Dental, Vision, Basic Life, Short Term Disability and Long-Term Disability Coverage
• Paid Parental Leave
• Support and Community Involvement
• 14 Paid Company Holidays
• Unlimited Paid Time Off for Exempt Employees
• 96 Hours of Sick Time and 120 Hours of Vacation for Non-Exempt Employees Accrued Each Year

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