Staff Product Data Scientist

Key Responsibilities

• Experimentation & Optimization: Design, execute, and analyze rigorous A/B tests to optimize the consumer product experience and drive user engagement
• Proactive Analysis: Independently identify hidden problems and growth opportunities through deep-dive data exploration
• Insight Visualization: Build and maintain high-fidelity dashboards to track critical KPIs and visualize complex market and user behaviors
• Predictive Modeling: Develop sophisticated models to understand user behavior and predict outcomes in a volatile, real-time environment
• Cross-Functional Collaboration: Partner directly with product and engineering teams to implement data-driven solutions and ensure technical feasibility
• Project Ownership: Drive data initiatives from initial problem identification through to solution implementation and post-deployment measurement
• Technical Communication: Translate complex statistical findings into clear, actionable narratives for both technical and non-technical stakeholders
• Methodological Standards: Help establish and refine the organization's data best practices and analytical methodologies

Work Style & Environment

• In-Person Collaboration: This role is based in-person at our client's office
• Intensity: Candidates must be comfortable with unconventional hours and an intense, high-velocity pace where expectations are high and impact is immediate

Requirements

• Professional Experience: 3+ years of Data Science experience within a startup, high-growth scale-up, or FAANG-tier environment
• Technical Stack: Advanced proficiency in Python or R, alongside mastery of SQL (specifically within BigQuery environments)
• Experimentation Mastery: Strong experience in the end-to-end lifecycle of designing and analyzing A/B tests for high-traffic consumer products
• Execution & Agency: Demonstrated ability to work autonomously, managing entire project lifecycles from ideation to implementation without constant oversight
• Communication: Exceptional ability to synthesize data insights into actionable business recommendations

Preferred Qualifications

• Domain Expertise: Direct experience with cryptocurrency, blockchain data, or fintech/consumer tech products
• Advanced Visualization: High-level skills in data visualization tools (e.g., Omni, Looker)
• Statistical Rigor: Advanced knowledge of causal inference and complex statistical methods
• Data Engineering: Experience building and maintaining data pipelines using modern tools such as Dagster or dbt
• Machine Learning: Familiarity with ML methods and their practical applications in product environments