Staff Data Scientist, Finance Analytics - SaaS

Staff Data Scientist, Finance Analytics - SaaS

Location: San Francisco, CA (US Remote Eligible)

Compensation: $180-240k base + equity

Are you ready to drive high-impact decisions at the intersection of finance and data? Join a rapidly growing Series E company at the cutting edge of AI-powered web development, and help shape the future of technology innovation.

We’re looking for a Staff Finance Data Scientist to take charge of financial analytics initiatives, bridging the gap between Finance and Data teams. In this role, you’ll be instrumental in creating trusted financial models, designing impactful forecasts, and delivering strategic insights that will guide key business decisions and fuel our continued growth.

What You’ll Do:

• Build and maintain dbt models in Snowflake, transforming raw product telemetry into clear financial views (ARR, margin, unit economics).
• Use Python-driven Monte Carlo and statistical models to forecast revenue, costs, and gross margin under multiple scenarios.
• Dive deep into revenue, COGS, and operating expenses, explaining plan vs. actual variances and identifying key business drivers.
• Collaborate with Product Monetization to model the impact of new pricing tiers, overage bands, and feature gates.
• Develop self-serve dashboards (e.g., Hex, Mode, Looker) trusted by Finance, ELT, and Board stakeholders during the month-end close.
• Define and implement data-quality SLAs, ensuring that all revenue and cost metrics are fully auditable.
• Provide best-practice guidance on dbt design patterns, Snowflake optimization, and Python analytical tooling for analysts and engineers.

What We’re Looking For:

• 7+ years in analytics or data science roles, with a focus on finance (experience with SaaS or usage-based business models preferred).
• Hands-on experience with dbt (production models, testing, CI/CD) and Snowflake (performance tuning, RBAC, cost management).
• Strong proficiency in SQL and Python (pandas, scipy/statsmodels, Prophet) for forecasting, scenario modeling, and statistical analysis.
• Experience with BI tools such as Looker, Hex, Mode, Tableau.
• Deep understanding of SaaS/cloud economics including MRR/ARR, COGS allocation, gross margin, LTV/CAC, churn, and cohort retention.
• Proven track record in building usage-based pricing models and forecasting frameworks from raw event data.
• Ability to convey complex data insights to executive audiences and collaborate effectively with engineers.
• Bachelor’s or Master’s in Finance, Economics, Statistics, Data Science, or a related field.