About the Role:

Gusto is looking for an experienced, hands-on people manager to lead a core Data Science & Analytics team. This role sits at the heart of how we use data — and increasingly AI — to understand, shape, and scale Gusto's products. You’ll both manage a team of data scientists and analysts as well as personally get in-the-weeds to work closely with Product, Engineering, Design, Marketing, Sales, and Finance to deliver insights and frameworks that inform strategy, optimize user experiences, and accelerate business growth.

We're looking for a leader who can balance strategic influence with hands-on craft — someone who can guide senior Gusto leaders through data and AI strategy, coach data scientists on impactful problem solving, and dive in to drive forward statistically rigorous analyses when needed.

Here’s what you’ll do day-to-day:

• Lead and develop a team of data scientists – hire, empower, and coach team members; set a high bar for analytical quality and career growth.
• Shape product and business strategy through data – partner with Product and cross-functional leaders to identify opportunities, prioritize investments, and influence long-term product roadmaps.
• Develop and scale measurement frameworks – define key metrics, design monitoring systems, and ensure product initiatives — including AI-powered features — are rigorously tracked and evaluated.
• Support experimentation and decision-making – support inferential analyses and experimentation (e.g., A/B tests, segmentation, funnel analysis), including designing evaluations for AI and ML-driven systems, ensuring findings are actionable and aligned to strategic goals.
• Partner on AI-powered product development – collaborate with ML Engineering and Product to bring intelligent features to life (personalization, predictions, intelligent automation), ensuring they're grounded in customer insight and measured for real-world impact.
• Balance strategic and hands-on impact – dive deep into data, review and refine analyses, and ensure insights are both technically sound and business-relevant.
• Influence senior leadership – communicate insights and recommendations clearly, framing trade-offs and shaping executive decision-making.

Here’s what we're looking for:

• 10+ years of experience in data science or related fields, with at least 4 years managing and scaling high-performing data science teams.
• Deep expertise in product analytics – experience with user acquisition, activation, retention, engagement, or expansion in SaaS or product-led environments.
• Technical fluency – advanced coding skills, strong statistical reasoning, and familiarity with experimentation frameworks; ability to mentor data scientists on best practices.
• AI product intuition – experience working at the intersection of data science and AI product development; comfort reasoning about model behavior, evaluation design, and the tradeoffs of deploying AI in customer-facing contexts.
• Strategic and business acumen – demonstrated ability to connect insights to product and business goals, and to influence roadmaps through data.
• Executive communication skills – proven experience presenting insights to senior stakeholders, turning complex data into clear and actionable recommendations.
• Cross-functional collaboration – history of working closely with Product, Engineering, and go-to-market teams to drive decisions and deliver impact.
• Hands-on experience with ML applications in product contexts (e.g., personalization, churn prediction, customer segmentation, or LLM-powered features) is strongly preferred.
• Familiarity with multi-product SaaS ecosystems and customer lifecycle analytics is desirable.

Our cash compensation amount for this role is targeted at $217,000 - $265,000 in 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.

About the Role

The Revenue Operations team at Gusto is a full-stack team responsible for data, analytics, and operational excellence in pursuit of scaling our revenue growth. The Go-To-Market Analytics team is one functional area, responsible for defining and owning the metrics for scaling our Sales teams. 

Gusto is looking for a Revenue Analytics Engineer to build and maintain foundational data infrastructure that is crucial to growing and scaling our Sales efforts. In this role, you will partner with our GTM analysts to scope and deliver data products for an audience ranging from company and revenue leadership to operational and frontline sales. In doing so, you will own significant portions of our sales data from end-to-end, focusing on the transformation, design, and visualization workflows. In addition, you will establish best practices for systems design and workflows to maximize usefulness of AI at scale. 

This role will report to the Head of Go-To-Market analytics, and partner closely with Data Science, Data Platform, and Business Technology teams. 

Here’s what you’ll do day-to-day:

• Establish relationships with internal stakeholders to determine business needs, scoping and delivering solutions through data products
• Design, build, and maintain data pipelines and dashboards to automate “keep the lights on” work out of manually-managed processes
• Build a data foundation by incorporating business logic into raw data tables, laying the groundwork to enable value-add insights
• Create a dynamic reporting environment based on stakeholder needs
• Identify data discrepancies and set best practices for data logic to create a clean and well-documented environment
• Collaborate with broader data organization as steward to the definition and process management of core Gusto metrics

Here’s what we're looking for:

• Education or work experience in Engineering or Computer Science, or a related technical field 
• 7+ years of experience in an analytics engineering, business intelligence, or technical data analytics role
• Experience with SQL and ETL optimization techniques, especially within cloud-based data warehouses like Redshift, Snowflake, etc.
• Command-line experience and familiarity with version control collaboration tools (git)
• Experience with data pipeline management technologies with dependency checking, such as Airflow, as well as schema design and data modeling tools (dbt)
• Experience with data visualization technologies, e.g., Tableau, Looker, Sigma, Mode, Hex
• Experience with Python and data ingestion tools
• Ability to problem-solve open-ended problems and project manage dependencies and timelines to optimal outcomes
• Ability to demonstrate tools, business intuition, and attention to detail for data validation and QA 

Our cash compensation amount for this role is targeted at $138,000-156,000 in Denver & most remote locations, and $168,000-189,000 in New York & San Francisco Bay Area. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

The Data Engineering team builds tools and systems that make Gusto's data consistent, user-friendly, and helpful. This helps our teams make decisions using data and provide intelligent, customized experiences to our customers.

We're looking for a Senior Data Engineer who can take loosely defined problems and drive them end-to-end—from framing the problem and aligning stakeholders to designing, building, and delivering durable data solutions. You’ll partner closely with analytics, product, and engineering teams to deliver data solutions that drive real business and customer impact.

Preferred Qualifications

• 8-10+ years of industry experience in data engineering building scalable data pipelines and data products
• Strong proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java)
• Proven experience building and maintaining robust data pipelines and ETL workflows, with hands-on dbt experience for reliable, testable, and maintainable data transformations.
• Hands-on experience ingesting data from diverse sources, including APIs, databases, SaaS applications, and event streams.
• Strong foundation in data modeling, schema design, and data quality best practices, with functional experience working on cloud platforms like Snowflake, Redshift, BigQuery, or Databricks.
• Experience implementing CI/CD pipelines, automated testing, and data observability to ensure reliability and trust in data systems
• Familiarity with monitoring, alerting, and incident response for production-grade data pipelines
• Proven ability to optimize performance and cost across data workflows and storage systems
• Functional understanding of how to leverage AI and automation in data engineering — building self-service tools, intelligent pipelines, and agents that automate repetitive tasks
• Exemplar problem-solving skills and ability to work collaboratively in cross-functional teams.
• Strong communication and collaboration skills, with a focus on clarity, empathy, and shared ownership

Compensation Details

Our cash compensation amount for this role is targeted at $155,000-$185,000/yr in Denver, $170,000-$200,000/yr in Los Angeles, and $190,000-$220,000/yr 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.

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.

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.