Senior Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Serve as an integrated Data partner with Product, Design, and Engineering, influencing strategy, product proposals, and experiments.

• Develop analytical frameworks throughout the product-led growth lifecycle, covering acquisition, activation, engagement, adoption, expansion, monetization, and sustainability.

• Employ funnel, cohort, journey, and sequence analysis to pinpoint friction points and areas for enhancement.

• Recognize behaviors and milestones that forecast conversion, production readiness, expansion, churn, and long-term customer success.

• Examine patterns of feature discovery and adoption, recommending interventions that promote increased adoption and expansion.

• Design and assess experiments and product modifications using matched comparisons, pre/post-intervention analysis, causal methods, and other relevant techniques.

• Differentiate between observed outcomes and assumptions, quantify uncertainty, and articulate the level of confidence behind conclusions.

• Prioritize growth opportunities based on potential impact, confidence, effort, and the feasibility of measurement.

• Create reusable datasets, metrics, dashboards, and analytical tools for Product, Marketing, Sales, and leadership teams.

• Collaborate with Engineering and Data Engineering to enhance event instrumentation, data quality, and analytical models.

• Present findings through visualizations, written narratives, and actionable recommendations.

• Review onboarding signals and suggest appropriate instrumentation.

• Establish reporting and repeatable analysis frameworks for product-led growth experiments.

• Analyze user behavior following the initial successful Activity or Workflow.

• Identify production-readiness signals and instances where users encounter obstacles.

• Chart feature-adoption pathways across key product areas.

⛳️ Requirements

• Solid foundation in statistics, experimental design, causal reasoning, and quantitative analysis.

• Experience utilizing product, behavioral, or event data to enhance activation, engagement, retention, conversion, or expansion.

• Familiarity with working with small samples, noisy signals, imperfect control groups, or scenarios where standard A/B testing is not always feasible.

• Strong judgment in choosing methods that are suitable for the decision at hand, the data available, and the associated uncertainty.

• Proficient in SQL and Python for analysis, modeling, and automation tasks.

• Experience with cohort analysis, funnel analysis, segmentation, predictive modeling, and both supervised and unsupervised machine-learning techniques.

• Ability to prototype in notebooks and transform recurring analyses into dependable data products, models, or workflows.

• Proficient with modern data platforms and query engines such as Athena, Presto/Trino, BigQuery, or Snowflake.

• Familiar with cloud and object storage technologies like AWS S3.

• Experience in creating dashboards and reusable analytical assets within a contemporary business intelligence platform.

• Comfortable navigating evolving definitions, incomplete instrumentation, and the trade-offs between analytical precision and decision-making usefulness.

• Proven track record of translating analysis into actionable product or business initiatives.

• Excellent communication skills, including the ability to explain methods, uncertainties, and recommendations in clear and accessible language.

• Curiosity about developer platforms, cloud infrastructure, usage-based products, and the complexities of product adoption.

• Capable of collaborating with teams across Product, Engineering, Marketing, Sales, Finance, and Data.

🏝️ Benefits

• Equity

• AI interview recording opt-out option without affecting candidacy

• Commitment to equal opportunity and reasonable accommodation support