Staff Data Scientist, Risk
$154k - $189kGusto
About Gusto
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.
All full-time employees receive competitive base pay, benefits, and equity (RSUs) — because everyone who helps build Gusto should share in its success. Offer amounts are determined by role, level, and location. Learn more about our Total Rewards philosophy .
AI is a fundamental part of how work gets done at Gusto. We expect all team members to actively engage with AI tools relevant to their role and grow their fluency as the technology evolves. AI experience requirements vary by role and will be assessed during the interview process.
About the Role:
As a Staff Data Scientist supporting Risk, 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’ll be working with an established team and risk leaders in Engineering, Product, Design, Operation, Identity and Compliance. You'll define and track metrics that help us understand our business performance, and dive deep into our risk stack 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.
Here’s what you’ll do day-to-day:
- Partner and Execute: Translate ambiguous stakeholder questions into clear, testable analyses. Structure complex business problems, identify drivers of performance, and communicate actionable insights to influence product or business decisions.
- Analytical Depth: Use sound statistical reasoning and experimentation frameworks to separate signal from noise. Select appropriate analytical techniques that balance rigor and speed, and leverage AI-assisted analytics to surface drivers of product performance, separating signal from noise.
- Experimentation & Measurement: Design and interpret experiments within your domain. Work with stakeholders to define success metrics, measure impact, and communicate trade-offs.
- Communication: Tell clear, data-driven stories that connect findings to business strategy. Adapt communication for technical and non-technical audiences.
- Execution: Own end-to-end delivery of analyses and metrics for your product area. Collaborate with cross-functional peers to scope, prioritize, and deliver insights that inform decisions.
Here’s what we're looking for:
- 7-10 years of experience in Data Science at a product-focused software company.
- Experience with Risk DS and risk modeling is strongly preferred.
- Strong SQL skills and comfort with Python.
- Proven ability to apply statistical methods, causal inference, and experimental design to real business problems.
- Excellent communication skills, with a track record of influencing cross-functional stakeholders and leadership.
- Demonstrated experience leading 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.
Our cash compensation amount for this role is targeted at $154,000/yr - $189,000/yr in Denver, and $186,000/yr - $230,000/yr 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.
Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale.
Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas.
When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. This includes non-office days for hybrid employees.
Our customers come from all walks of life and so do we. We hire great people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger. If you share our values and our enthusiasm for small businesses, you will find a home at Gusto.
Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you.
Gusto takes security and protection of your personal information very seriously. Please review our Fraudulent Activity Disclaimer .
Personal information collected and processed as part of your Gusto application will be subject to Gusto's Applicant Privacy Notice .
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