Why This Job is Featured on The SaaS Jobs
This Data Scientist role sits at the intersection of product analytics and core SaaS workflows, focused on the systems that determine how customers experience benefits and HR inside a software product. In the SaaS ecosystem, that “core product” remit tends to be where measurement discipline matters most, because small changes to onboarding, eligibility flows, or self-serve experiences can compound across a large customer base.
The career value here comes from building repeatable decision frameworks rather than one-off analyses. The emphasis on experimentation, causal inference, and metric definition maps directly to how modern SaaS companies run product development, prioritization, and forecasting. Working as the embedded data partner across Product, Engineering, Design, and Finance also develops the cross-functional influence that becomes increasingly important at senior levels in SaaS, where data science is expected to shape roadmaps and trade-offs.
This position is best suited to a practitioner who prefers ambiguous problem spaces and is comfortable being the accountable owner of measurement in a domain. It will fit someone who enjoys translating statistical rigor into decisions for mixed technical audiences, and who wants a role where mentoring and scaling analytics practices are part of the craft, not a side project.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Role:
Gusto is looking for a highly skilled and motivated Data Scientist to join our Core Products Data Science team. In this role, you'll leverage experimentation, statistical inference, and causal analysis to drive strategic decisions that shape how small businesses manage their benefits and HR experiences. The ideal candidate is a trusted data storyteller with strong statistical and coding skills, and a genuine passion for building products that make work better for employers and employees alike.
About the Team:
You'll work closely with Product, Engineering, Design, and Finance partners embedded in our Benefits and HR Experiences teams — becoming the go-to data expert for your domain, defining and tracking metrics that reflect product health and customer outcomes, and surfacing insights that inform roadmap decisions. You'll also integrate AI-assisted practices to expand the reach and rigor of your analysis across the organization.
We have multiple senior roles open on our Core Products Data Science team: one role supports Gusto's Benefits product team, and one supporting Gusto HR Experiences product team.
Here’s what you’ll do day-to-day:
- 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.
Here’s what we're looking for:
- 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 $155,000/yr - $220,000/yr in Denver, and $190,000 - $265,000 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.
