Staff Data Scientist - Growth + Core Products

At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff — payroll, health insurance, 401(k)s, and HR — so owners can focus on their craft and their customers. With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve.

Gusto is looking for highly skilled and motivated Data Scientists with extensive experience (7+ years) applying their expertise in a business environment. As a Staff Data Scientist, you will play a crucial role in leveraging experimentation, statistical inference, and causal analysis to drive strategic decision making that contributes to the overall success of our organization. The ideal candidate is a trusted data storyteller with strong statistical and coding skills, and a passion for applying these skills to help small businesses thrive.

In this role you will work closely with our Product, Engineering, Design, Finance, and other Data teams to become an expert in the data for your domain, define and track metrics that help us understand our business performance, and dive deep into our Payroll, Benefits, and HR data to deliver insights and answer questions. You’ll also integrate AI-assisted practices to accelerate analysis, enhance rigor, and expand the reach of insights across Gusto.

We have multiple senior roles open on both our (1) Growth and (2) Core Products data science teams. 

• →Lead: Own ambiguous problems, design analysis frameworks, and introduce structure that scales across multiple product domains.
• →Strategic Partnership: Collaborate with product managers, engineering leads, designers, and operations teams to proactively identify opportunities, align on strategy, and guide data-informed decision-making.
• →Analytical Rigor: Apply advanced statistical methods, causal inference, experimentation, and AI-assisted analytics to surface drivers of product performance, separating signal from noise.
• →Experimentation & Measurement: Design, analyze, and interpret experiments; ensure insights highlight trade-offs and limitations based on sample size and data quality.
• →Execution: Deliver multiple high-impact projects, balancing trade-offs to maximize business value, and maintain clear expectations of deliverables and timelines.
• →Communication: Present complex findings in a structured, compelling way to technical and non-technical stakeholders, fostering a data-informed mindset across the company.
• →Independence: Work with minimal guidance to prioritize, create, and deliver data science roadmaps, proactively resolving conflicts or misalignment across stakeholders.
• →Scaling the Craft: Mentor other data practitioners, up-level team best practices in experimentation, statistical modeling, and metric interpretation. Drive improvements in data quality, rigor, and adoption of better data capabilities leveraging AI-native tools and workflows across the org.

• 7–10 years of experience in Data Science at a product-focused software company.
• Strong SQL skills and comfort with Python
• Proven ability to apply statistical methods, causal inference, AI tools, and experimental design to real business problems.
• Excellent communication skills, with a track record of influencing cross-functional stakeholders and leadership.
• Demonstrated experience leading large, technically complex projects with clear business impact.
• A proactive, resilient problem-solver who independently structures ambiguous problems into actionable insights.
• Passion for mentoring others and raising the bar for data science craft across the team.
• BS/MS/PhD in a quantitative field (Statistics, Economics, Computer Science, Applied Math, etc.) or equivalent industry experience.

Our cash compensation amount for this role is targeted at $154,000/yr - $181,000/yr in Denver, and $175,000/yr - $225,000 for San Francisco and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.