Data Scientist

You Will

• Own performance measurement for your subdomain: monitoring the metrics that matter (wins, new revenue, funnel conversion, rep productivity), reporting against plan, and presenting the story in business reviews with sales leadership
• Lead investigations into performance questions ("why is X down?", "how can we improve Y?"), decomposing KPIs from first principles and designing experiments to test what actually works
• Take on large, ambiguous projects autonomously: scoping the problem, finding the right data, thinking critically about what it can and can't tell you, and landing the results with stakeholders
• Own and evolve your subdomain's data foundation, and partner with Sales DS peers on shared metrics, attribution logic, and cross-cutting analyses
• Translate data into business context: telling the story behind the numbers, pushing back on hypotheses with evidence, and building trust with senior sales, finance, and operations leaders
• Work AI-natively: use agents throughout your workflow and pioneer new ways of applying AI to the hardest problems in the sales domain
• Build self-serve dashboards and datasets that let the sales org answer its own questions
• Raise the bar for the team's analytical rigor, communication, and AI-enabled ways of working

You Have

• Minimum of 8 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or a PhD with 3 years experience; or equivalent experience
• Advanced SQL and strong Python; comfort owning the full stack from ETL to analysis to visualization
• Strong statistical foundations: experiment design, causal inference, funnel and cohort analysis, and forecasting; you can interpret results with rigor and explain the concepts behind them
• A track record of running large projects end to end with minimal direction; you're the person leadership trusts when the numbers matter
• Strong critical thinking: you know when to move fast and when to slow down on a problem with big consequences, and you pressure-test your own conclusions
• Exceptional communication: you can present performance to executives, translate technical nuance for non-technical partners, and write analysis documents that stand on its own
• Enthusiasm for building with AI, and curiosity about how far it can be pushed in data science work
• Curiosity about unfamiliar data and how sales organizations actually work, and the empathy to partner well with the people on the frontline

Nice to Have

• Prior experience supporting sales, GTM, or revenue organizations
• Familiarity with fintech, payments, or the SMB merchant space

We value strong fundamentals and curiosity over industry background; we'll teach you our domain.

Technologies We Use and Teach

• SQL, Snowflake, Databricks, Python (Pandas, NumPy)
• Looker, Omni, Airflow, dbt-style ETL patterns
• Agentic AI: agent skills and bots, automated reporting workflows, in-house tooling
• Salesforce and the modern GTM data stack
• A/B, matched-market, and causal testing