About the job
About Gusto
At Gusto, we are dedicated to empowering the small business economy. We take care of essential services such as payroll, health insurance, 401(k)s, and HR, allowing business owners to concentrate on their passion and serving their customers. With teams based in Denver, San Francisco, and New York, we proudly support over 400,000 small businesses nationwide, and we are committed to building a workplace that reflects and celebrates the diversity of our customers. Discover more about our Total Rewards philosophy.
About the Role:
We are seeking a highly skilled and motivated Staff Data Scientist with a minimum of 7 years of experience in a business environment. In this pivotal role, you will utilize experimentation, statistical inference, and causal analysis to drive strategic decision-making that enhances our organization's success. The ideal candidate is a trusted data storyteller with strong statistical and programming skills, passionate about using these abilities to support small businesses in thriving.
About the Team:
In this position, you will collaborate closely with our Product, Engineering, Design, Finance, and other Data teams to become an expert in your domain's data, define and track metrics that provide insights into our business performance, and delve into our Payroll, Benefits, and HR data to deliver valuable insights and answer critical questions. You will also implement AI-assisted methodologies to accelerate analysis, enhance rigor, and broaden the impact of insights throughout Gusto. We have multiple senior roles open, each focusing on a different segment of our business.
Here’s what you’ll do day-to-day:
- Lead: Tackle ambiguous challenges, design analytical frameworks, and introduce scalable structures across multiple product domains.
- Strategic Partnership: Work alongside product managers, engineering leads, designers, and operations teams to proactively identify opportunities, align on strategies, and steer data-informed decision-making.
- Analytical Rigor: Employ advanced statistical methods, causal inference, experimentation, and AI-assisted analytics to identify product performance drivers, distinguishing signal from noise.
- Experimentation & Analysis: Conduct rigorous experimentation to validate hypotheses and inform product iterations.

