Why This Job is Featured on The SaaS Jobs
This Principal Data Scientist role sits at the intersection of product analytics and decision science, a core capability for mature SaaS businesses that run on recurring revenue and measurable customer outcomes. The emphasis on experimentation, causal inference, and metric integrity signals work that directly shapes how a product organization learns, prioritises, and evaluates trade offs across multiple domains.
For a SaaS career, the long-term value is in building repeatable frameworks rather than one-off analyses. Leading analytical strategy, defining success metrics, and scaling approaches across teams are experiences that translate across product-led and platform SaaS companies. The remit also reflects modern SaaS data practice, where AI-assisted analysis is used to increase throughput while maintaining statistical rigor and clear storytelling for stakeholders.
This position is best suited to a senior data scientist who prefers high-leverage, cross-functional influence over narrow model-building ownership. It fits someone comfortable turning ambiguous business questions into measurement plans, aligning leaders around evidence, and raising analytical standards through mentorship. Remote flexibility across major hubs also suggests a role designed for collaboration across distributed product and engineering partners.
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 highly skilled and motivated Data Scientists with extensive experience (10+ years) applying their expertise in a business environment. As a Principal 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, each focused on a different area of our business
Here’s what you’ll do day-to-day:
- Strategic Leadership: Shape the analytical strategy for a major product or business area. Identify high-leverage opportunities, set long-term measurement and experimentation direction, and align executive stakeholders around data-driven priorities.
- Execution Excellence: Drive and execute on org-level analytical roadmaps that shape company strategy. Achieve alignment and ensure consistent analytical rigor and metric integrity across product domains.
- Scaled Impact: In addition to being an expert in statistical methods and driving impact through execution, you will drive frameworks for experimentation, causal analysis, and metric design that scale across multiple teams and influence org-wide decision quality.
- Thought Partnership: Serve as a trusted advisor to senior product, engineering, and business leaders. Anticipate emerging questions, proactively define success measures, and advocate for data-informed strategy across the org.
- Analytical Innovation: Push the boundaries of statistical modeling, experimentation, and AI-assisted analytics. Design methods and tools that expand how Gusto leverages data to drive customer and business impact.
- Mentorship: Mentor and coach more junior data scientists, raising the bar for analytical thinking and storytelling.
Here’s what we're looking for:
- 10+ years of experience in Data Science at a product-focused software company.
- Strong SQL and Python skills.
- Proven ability to apply statistical methods, causal inference, and experimental design to real business problems.
- Experience developing Machine Learning models is a plus.
- 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 $170,000/yr - $210,000/yr in Denver, $185,000/yr - $225,000/yr in Los Angeles, $200,000/yr - $240,000 for San Francisco, Seattle and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.