Principal Data Scientist - Product Analytics

About this role

ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen–fast.

Overview

We are seeking a Principal Data Scientist to lead ZoomInfo's product analytics function and own our measurement systems across the product portfolio. This is a technical leadership role for someone who is fundamentally an exceptional analyst first - someone obsessed with understanding customer behavior through data, with the ability to influence strategy through insights.

This role combines hands-on analytical depth with strategic scope. You'll design measurement frameworks, conduct deep-dive investigations, and drive product decisions through data. While we're particularly interested in candidates with PLG experience, what matters most is your ability to rapidly understand any product domain, ask the right questions, and uncover insights that shape business outcomes.

The ideal candidate is an analytically relentless someone who writes clean SQL, thinks statistically, debugs data problems obsessively, and translates findings into clear business narratives. You're comfortable in ambiguity, own investigations from scratch, and build scalable analytical systems. Leadership here means elevating analytical standards and being a trusted data partner to Product, Engineering, and business teams.

What You'll Do

Product Measurement & Analytics Architecture

• Design and own measurement frameworks that connect customer behavior to business outcomes (activation, adoption, monetization, retention, expansion, churn)

• Establish source-of-truth definitions for key metrics and KPIs across product lines

• Build scalable reporting infrastructure and dashboarding systems that minimize manual overhead

• Develop leading indicators that predict customer success and business impact

• Ensure measurement consistency and data quality across teams and business units

Deep-Dive Investigation & Diagnostics

• Conduct rigorous root-cause analyses on significant changes in product performance or business metrics

• Investigate customer behavior patterns, friction points, and conversion barriers across the customer journey

• Build customer segmentation frameworks that reveal behavioral differences and predict outcomes

• Identify the behaviors and product experiences most strongly associated with customer success

• Translate complex analyses into clear business narratives that shape decisions

Growth & Product Insights

• Quantify opportunity size and identify high-leverage areas for product investment

• Support experimentation efforts by designing test frameworks and evaluating results with statistical rigor

• Build analytical frameworks that help teams prioritize investments across the customer lifecycle

• Advise Product and GTM leadership on customer trends, adoption patterns, and growth opportunities

• Measure business impact of major product initiatives and roadmap decisions

AI-Native Analytics & Operational Excellence

• Redesign analytics workflows to leverage AI tools (Claude, automation, etc.) for faster investigation and scaled insights

• Build systems that continuously monitor product performance and surface anomalies proactively

• Develop scalable self-service analytics capabilities while maintaining data governance and trust

• Establish workflows that reduce manual effort and increase speed-to-insight

• Stay current with emerging AI capabilities and incorporate them into your analytical toolkit

Cross-Functional Leadership

• Partner with Product, Engineering, GTM, and executive teams as a trusted data advisor

• Elevate analytical standards and build a culture of rigorous, data-informed decision-making

• Lead initiatives from opportunity identification through execution and impact measurement

• Influence senior stakeholders through data storytelling and clear business context

About You

• You think in systems and causality, not just dashboards - you ask "why" until you understand the mechanism

• You're intellectually restless about data quality and will debug a data pipeline issue as readily as conducting analysis

• You're curious about how products drive customer adoption, monetization, and retention

• You balance technical depth with business judgment and stakeholder communication

• You enjoy the full arc: framing ambiguous problems, designing investigations, executing analysis, and translating findings into action

• You actively use analytical tools and automation (including AI) to scale your impact and accelerate insights

What You Bring

• 8+ years of experience in Product Analytics, Growth Analytics, Data Science, or related analytical fields

• Expert-level SQL and Python skills - you write clean, efficient code and debug data issues independently

• Strong statistical foundation - you understand experimental design, significance testing, and know when correlations mislead

• Demonstrated ability to lead large-scale analytical initiatives with measurable business impact

• Deep experience conducting investigations into customer behavior, product performance, and business outcomes

• Ability to translate complex data into clear, actionable business recommendations and influence decisions

• Project management discipline - you own scope, prioritize ruthlessly, and ship insights that drive action

• Strong fundamentals in building scalable systems - reporting infrastructure, monitoring, data pipelines, dashboards

Preferred Qualifications

• Experience in Product-Led Growth or self-serve SaaS (Figma, Notion, Slack, Linear, Calendly, etc.) - you understand activation loops and freemium economics

• SaaS customer lifecycle analytics - you can map the full journey from trial to expansion

• Proficiency with analytics stack -…