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Data Scientist, Risk

Location
San Francisco, CA - Hybrid
Compensation
$133k–$193k/yr
Level
senior
Type
full time · Hybrid

Posted by employer 6 months ago

First seen on Joblaze 5 months ago

Last verified on the company career page 14 hours ago

Skills & Technologies

Requirements

Experience
5–7 years

Not disclosed in this posting: visa sponsorship.

Benefits

401k Match Equity/Stock Options Health Insurance

Joblaze summary

In the role of Staff Data Scientist for Risk at Gusto, the individual will focus on translating complex business challenges into actionable insights through statistical analysis and experimentation. Proficiency in SQL and Python, along with a strong background in risk modeling, are essential for success in this position. This role is ideal for seasoned data scientists with 7-10 years of experience who excel in cross-functional collaboration and possess a knack for storytelling with data. The team emphasizes the integration of AI tools to enhance analytical rigor and expand the impact of insights across the organization.

Joblaze insights

  • Listed about 5 months ago — first seen on Joblaze May 3, 2026. Last confirmed on Gusto's careers page October 8, 2026.
  • Salary band is below the typical range for Data Science roles (median ~$175,000).
  • Starts above 12% of 60 comparable senior data science roles in United States that list Python we track (median $175,000 across 37 companies). See Python salary trends
  • Python appears in 70.2% of 114 comparable senior data science roles in United States; AI/ML appears in 11.4% of 114 comparable senior data science roles in United States.

Quick facts

Is the Data Scientist, Risk role remote?
It's hybrid — Gusto expects some on-site time in San Francisco, CA - Hybrid.
What's the salary range?
Gusto lists $133,000–$193,000 for this role.
How much experience is required?
5–7 years of relevant experience for this Data Scientist, Risk role.
Where is the role based?
Gusto is hiring for this position in San Francisco, CA - Hybrid.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI/ML, Python, SQL.
What seniority level is this role?
Gusto targets senior candidates for this position.
Is this full-time or contract?
Full-time for this Data Scientist, Risk role at Gusto.

From the original posting


About Gusto

About the Role:

As a 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. This role is an equivalent of Staff-level, with an expectation of owning experimentation and building risk models that will have direct impact on business decisions.

This is a San Francisco-based role with expectations to be in office Tuesdays and Wednesdays.

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
  • Build Models and Leverage AI: use Claude Code to enhance analytical approaches. Build risk models and present recommendations to process and project enhancements
  • 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.
  • 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 $186,000/yr - $230,000/yr for San Francisco. 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.

Standard company text repeated across Gusto's postings is omitted here.

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