Lead Data Scientist

Job description

About Chestnut

Chestnut is building the first AI-native operating system for insurance distribution by transforming how the $1T+ insurance industry allocates its largest spend: sales and distribution.

Backed by a16z, we’re replacing legacy systems with a modern, flexible platform that helps carriers automate complex workflows, optimize every distribution dollar, and unlock new growth. We have major insurers under contract, and early adopters are expanding.

This is a generational platform shift. Recent advances in agentic AI make it possible to automate what was once manual and error-prone. We’ve spent years building the data model and context layer required to make this real, and now we’re scaling with urgency.

At Chestnut, we operate with the belief that small, high-context teams working with best-in-class tools and colleagues can achieve outsized results. We embody what it means to be AI-lean: chasing 10x productivity gains that allow us to scale impact beyond our headcount.

If you’re excited to modernize the infrastructure of one of America’s most essential industries, we’d love to meet you. Whether shaping core product experiences or laying the groundwork for intelligent automation, your work will accelerate a once-in-a-generation transformation.

Engineering at Chestnut

Chestnut is a technology company at its core, building the infrastructure to power the future of AI in insurance. Realizing that vision requires both a modern, reliable foundation and the intelligence layer on top. Our engineers work across this stack, from designing data models that capture the nuance of insurance workflows, to developing APIs that support intelligent automation, to shipping user-facing product experiences and early AI copilots.

As Lead Data Scientist, you’ll scale and lead a team of analysts and data scientists while building the systems, processes, and culture that turn insights into impact. You’ll partner closely with product, design, and founders to ensure we’re capturing the right data, appropriately analyzing that data to drive results, hiring best-of-the-best talent, and laying the foundation for long-term technical excellence.

What You’ll Do

  • Unlock data-driven decisions: Explore and analyze customer data to provide insights, create business value, and inform product decisions.

  • Build robust foundations: Collaborate and own end-to-end data workflows - from raw ingestion to analysis-ready pipelines - ensuring accuracy, consistency, and scale.

  • Predict the future: Develop and deploy models to forecast outcomes, detect anomalies, and personalize user experiences.

  • Be a thought partner: Bring a strategic lens to data by identifying data needs and shaping requirements.

  • Raise the bar: Introduce best practices in analytics, experimentation, and modeling, including mentoring others to build a data-fluent culture.

You Might Be a Fit If You…

  • Are fluent in SQL and Python and are comfortable owning data from ETL to modeling to visualization.

  • Have built dashboards and reports with tools like Looker, Power BI, or Tableau and know how to tell a clear story with data.

  • In partnership with engineering, have deployed predictive models into production and understand the full data lifecycle from data exploration to training to monitoring.

  • Are comfortable with statistical testing, causal inference, and experiment design.

  • Have worked in fast-paced, ambiguous environments and thrive when collaborating cross-functionally.

  • Are excited by open-ended problems and know how to prioritize ruthlessly to drive business impact.

What Success Looks Like in Your First 90 Days

  • Data stakeholders feel empowered and supported in making fast, informed decisions.

  • Forward-deployed implementation teams supported with thoughtful data strategy and project plan.

  • Key business questions - both for internal users and external customers - have been proactively answered through thoughtful analysis.

  • At least one high-impact predictive model is scoped, prototyped, or tested.

  • Teammates see you as a go-to partner for insights, strategic thinking, and leveling up their data instincts.

Benefits

  • Competitive salary and equity, with 10 year exercise window for stock options

  • Remote-first culture built on trust, autonomy, and high performance

  • Team offsites for all of us to bond

  • Take what you need vacation policy

  • Top notch health, dental, and vision insurance subsidized by us

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