Senior Product Data Scientist - Remote

About the Role

Key Responsibilities

• Champion the strategic vision for AI adoption by aligning initiatives with organizational goals to unlock value, drive competitive advantage, and ensure responsible, transparent, and impactful outcomes.
• Lead the ethical transformation of business processes and culture through AI integration that enhances efficiency, innovation, and decision-making.
• Lead end to end product lifecycle: discovery, requirements, prototyping, delivery, and post launch optimization.
• Translate customer problems and market signals into clear product strategies, roadmaps, and narratives.
• Define and own KPI frameworks (e.g., adoption, engagement, accuracy/quality, latency, reliability, ROI) and establish data contracts and telemetry with engineering.
• Build scalable analytics and reporting: specify event taxonomies, own dashboards, conduct deep dive analyses (SQL/BI), and communicate insights to executives.
• Partner with data science to set evaluation plans, interpret model results (at a product level), guide labeling/evaluation needs, and translate findings into user facing improvements.
• Run experiments (A/B, pilots, shadow tests); ensure clean baselines and statistically sound decisions.
• Drive cross functional execution and launch readiness; manage trade offs and organize work for timely GA and iteration.
• Ensure compliance/readiness with internal governance processes; maintain clear documentation and decision logs.
• Contribute to product culture: crisp writing, clear decision making, customer obsession, and outcomes orientation.

Requirements

• 3+ years of experience in data science or analytics discipline OR 3+ years of product management owning definition, delivery, and post launch optimization for analytics or AI enabled products.
• Experience defining metrics and instrumentation, partnering with engineering on event schemas/telemetry, and making roadmap decisions from data.
• Experience with experimentation methods (A/B tests, pilots) and interpreting results for product decisions.
• Demonstrated analytical fluency: structured problem solving, comfort querying data (SQL) and using BI tools (e.g., Power BI, Looker, Tableau); ability to create self serve dashboards and weekly business reviews.
• Proven solid product writing (PRDs, PR/FAQs, business cases) and stakeholder communication.
• Proven cross functional leadership with engineering, data science, design, and operations.

Nice to Have

• Experience with applied analytics in a regulated or complex domain (e.g., healthcare, fintech, insurance).
• Familiarity with ML productization and model evaluation at a product level (e.g., precision/recall trade offs, error analysis, data quality gates).
• Background with enterprise integrations, data interoperability, and event driven architectures.
• Proficiency with scripting (Python or R for ad hoc analysis/visualization) and feature telemetry best practices (latency SLOs, quality bars).

Qualifications

• Educational background is not explicitly specified, but experience in data science, analytics, or product management is required.

Benefits & Perks

• A comprehensive benefits package.
• Incentive and recognition programs.
• Equity stock purchase and 401k contribution.
• Salary range from $110,200 to $188,800 annually based on full-time employment.
• Additional benefits and incentives subject to eligibility.