Data Scientist, Strategic Finance

Join Rippling’s Strategic Finance team in San Francisco, CA (onsite), where you’ll use advanced analytics and practical AI tool development to support company-wide forecasting, planning-cycle decisions, and continued ARR growth. You’ll collaborate closely with Finance leaders while owning automated models, key business metrics, and the data infrastructure that powers dependable performance insights.

This role offers a competitive salary of USD 120,000 - 190,000 per year (US Tier 1), along with benefits + equity. Rippling also provides reasonable accommodations for candidates with disabilities who need assistance during the hiring process.

Responsibilities

• Lead analytics for company-wide planning cycles, partnering with Finance leaders to shape forecasts, financial targets, and resource allocation decisions
• Drive AI adoption across Finance by combining hands-on development with coaching to improve how analysis, insights, and decisions are produced
• Own automated forecasting models for key business metrics, including customer retention and expansion
• Define and deeply understand critical business metrics such as net dollar retention and customer acquisition cost
• Build high-quality data infrastructure to enable accurate analysis of business performance across sales, marketing, R&D, and customer experience
• Serve as a strategic partner to Finance executives with data-driven insights supporting strong ARR growth

Requirements

• 4+ years of experience in data science and analytics, with evidence of using data science methods to drive business impact in B2B SaaS or fintech
• Master’s degree or Bachelor's degree in Computer Science, Engineering, Statistics, Data Science, Econ, Math, Business Analytics, or a related field
• Proficiency with data analysis tools including Python, SQL, dbt, and Databricks, plus comfort running queries, performing statistical analysis, and building models
• Strong analytical and problem-solving skills to translate complex data into actionable insights for strategic decisions
• Curiosity and initiative to experiment with new AI tools and improve workflows
• Clear communication skills to share technical findings with both technical and non-technical stakeholders
• Strong ownership to drive projects end to end
• Ability to operate autonomously in an ambiguous, fast-paced environment

Preferred Qualifications

• End-to-end model lifecycle experience, including development, backtesting, deployment, and monitoring
• Time series forecasting with limited historical data
• Financial modeling experience gained through Strategic Finance, Investment Banking, or a close partnership with Finance teams

Tech Stack

Python, SQL, dbt, Databricks

Rippling considers working in the office, at least three days a week under the current policy, to be an essential function for office-based employees within a defined radius of a Rippling office.