Growth Data Science Leader

Gusto, Inc.•Denver, CO

7d•$185,000 - $255,000•Hybrid

About The Position

Gusto is looking for an experienced, hands-on people manager to lead a data science and analytics team supporting Growth product initiatives. This role sits at the heart of how we use data — and increasingly AI — to understand, shape, and scale Gusto's products. You’ll both manage a team of data scientists and analysts as well as personally get in-the-weeds to work closely with Product, Engineering, Design, Marketing, Sales, and Finance to deliver insights and frameworks that inform strategy, optimize user experiences, and accelerate business growth. We're looking for a leader who can balance strategic influence with hands-on craft — someone who can guide senior Gusto leaders through data and AI strategy, coach data scientists on impactful problem solving, and dive in to drive forward statistically rigorous analyses when needed. This role is the equivalent to a Senior Manager/Director-level role.

Requirements

10+ years of experience in data science or related fields, with at least 4 years managing and scaling high-performing data science teams.
Deep expertise in product analytics – experience with user acquisition, activation, retention, engagement, or expansion in SaaS or product-led environments.
Technical fluency – advanced coding skills, strong statistical reasoning, and familiarity with experimentation frameworks; ability to mentor data scientists on best practices.
AI product intuition – experience working at the intersection of data science and AI product development; comfort reasoning about model behavior, evaluation design, and the tradeoffs of deploying AI in customer-facing contexts.
Strategic and business acumen – demonstrated ability to connect insights to product and business goals, and to influence roadmaps through data.
Executive communication skills – proven experience presenting insights to senior stakeholders, turning complex data into clear and actionable recommendations.
Cross-functional collaboration – history of working closely with Product, Engineering, and go-to-market teams to drive decisions and deliver impact.

Nice To Haves

Hands-on experience with ML applications in product contexts (e.g., personalization, churn prediction, customer segmentation, or LLM-powered features) is strongly preferred.
Familiarity with multi-product SaaS ecosystems and customer lifecycle analytics is desirable.

Responsibilities

Lead and develop a team of data scientists – hire, empower, and coach team members; set a high bar for analytical quality and career growth.
Shape product and business strategy through data – partner with Product and cross-functional leaders to identify opportunities, prioritize investments, and influence long-term product roadmaps.
Develop and scale measurement frameworks – define key metrics, design monitoring systems, and ensure product initiatives — including AI-powered features — are rigorously tracked and evaluated.
Support experimentation and decision-making – support inferential analyses and experimentation (e.g., A/B tests, segmentation, funnel analysis), including designing evaluations for AI and ML-driven systems, ensuring findings are actionable and aligned to strategic goals.
Partner on AI-powered product development – collaborate with ML Engineering and Product to bring intelligent features to life (personalization, predictions, intelligent automation), ensuring they're grounded in customer insight and measured for real-world impact.
Balance strategic and hands-on impact – dive deep into data, review and refine analyses, and ensure insights are both technically sound and business-relevant.
Influence senior leadership – communicate insights and recommendations clearly, framing trade-offs and shaping executive decision-making.