Staff Data Scientist - Core Products

Gusto Gusto · Fintech · New York, NY +1 · Data

This role focuses on leveraging experimentation, statistical inference, and causal analysis to drive strategic decisions for Gusto's core products (benefits and HR experiences). The Data Scientist will partner with cross-functional teams, apply advanced statistical methods and AI-assisted analytics, design and analyze experiments, and communicate complex findings to stakeholders. The role also involves mentoring and improving team best practices, including the adoption of AI-native tools.

What you'd actually do

  1. Lead ambiguous problems, design analysis frameworks, and introduce structure that scales across multiple product domains.
  2. Collaborate with product managers, engineering leads, designers, and operations teams to proactively identify opportunities, align on strategy, and guide data-informed decision-making.
  3. Apply advanced statistical methods, causal inference, experimentation, and AI-assisted analytics to surface drivers of product performance, separating signal from noise.
  4. Design, analyze, and interpret experiments; ensure insights highlight trade-offs and limitations based on sample size and data quality.
  5. Deliver multiple high-impact projects, balancing trade-offs to maximize business value, and maintain clear expectations of deliverables and timelines.

Skills

Required

  • SQL
  • Python
  • statistical methods
  • causal inference
  • experimental design
  • communication skills
  • leadership
  • project management
  • problem-solving

Nice to have

  • AI tools

What the JD emphasized

  • 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.