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The Principal Data Scientist on the Payments team at Gusto is responsible for translating complex payment data into actionable insights and models that enhance payment products. This role involves collaborating with various teams to define metrics, drive experimentation, and build predictive models while integrating AI practices to improve analysis and insights.
Experience Level
Senior Level
Principal Data Scientist, Payments
Posted 1 weeks ago
Full-Time
Employment Type
Remote
Work Location
About This Role
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 400,000 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.
Small business owners trust Gusto with something fundamental: making sure their people get paid, on time, every time. As a Principal Data Scientist on the Payments team, you'll sit at the intersection of financial infrastructure and data science — translating the complexity of a high-scale payments ecosystem into the insights and models that shape how we build, operate, and improve our payments products.
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 payments 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 is a role for someone who's equally comfortable diving into ledger-level transaction data and standing in front of a payments engineering team to influence architecture decisions. If you want your work to directly protect and improve the financial lives of hundreds of thousands of small businesses, this is the role.
Here’s What You’ll Do Day-to-day
Own Payments Intelligence End-to-end
Design and maintain measurement frameworks for payment success rates, failure root causes, retry strategies, and settlement timing — becoming the authoritative source of truth for payments health across the org.
Partner With Payments Engineering
Embed with backend engineering teams to understand infrastructure constraints and data availability, translate that knowledge into well-scoped experiments, and influence roadmap prioritization with data-backed recommendations.
Drive Experimentation At Scale
Design and analyze A/B tests and quasi-experiments across payment flows — including retry logic, routing decisions, and failure recovery — ensuring statistical rigor even in low-conversion, high-variance payment environments.
Build Predictive Models
Develop and deploy models for payment failure prediction, risk scoring, and anomaly detection that operate at Gusto's transaction volume, partnering with Machine Learning Engineers and Product Engineers on productionization and monitoring.
Build Ai-native Data Products
Go beyond using AI to go faster; build data products and automated workflows with AI as a core component. Know what "good" looks like for a clustering model or automated workflow, when to trust the output, when to challenge it, and how to build guardrails that let the team scale AI use responsibly in a regulated financial context.
Own The Business Narrative
Be the person payments product and engineering leadership calls before an exec review, not after. Comfortable defending methodology on ARR projections, CX attribution, and cost savings in a room with skeptics. Translate nuanced statistical results and model outputs into clear, actionable narratives for payments engineers, product managers, finance partners, and executive leadership.
Here’s What We're Looking For
10+ years of experience
in Data Science or a closely related quantitative role at a product-focused software company, with meaningful exposure to payments, fintech, or financial infrastructure.
Deep Payments Domain Knowledge
Hands-on experience with payments infrastructure: ACH, card networks, bank integrations, settlement flows, or equivalent, with a strong intuition for how backend systems shape data availability and quality.
Strong SQL and Python skills
, with experience querying large-scale transactional datasets and building reproducible analytical pipelines.
Proven Experimentation And Causal Inference Expertise
Ability to design rigorous experiments in challenging payment contexts (rare events, high variance, non-stationarity) and communicate trade-offs clearly.
Ai-native Mindset
Has built data products and analytical workflows with AI as a core component, not just used AI to go faster. Knows what "good" looks like for a clustering model or automated workflow, when to trust the output, when to challenge it, and how to build guardrails that scale AI use responsibly in a financial context.
Cross-functional Influence
Track record of collaborating with and influencing backend engineers and technical stakeholders, not just product and business partners.
Our cash compensation amount for this role is targeted at $184,000/yr - $210,000/yr in Denver, and $217,000/yr - $250,000 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.
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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