Staff Data Scientist - Sales Analytics

Staff Data Scientist – Sales Analytics

Location: San Francisco (Hybrid)

Salary: $200–250k base + RSUs

This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We’re looking for a Staff Data Scientist to drive Sales and Go-to-Market (GTM) analytics, applying advanced modeling and experimentation to accelerate revenue growth and optimize the full sales funnel.

About the Role

As the senior data scientist supporting Sales and GTM, you will combine statistical modeling, experimentation, and advanced analytics to inform strategy and guide decision-making across our revenue organization. Your work will help leadership understand pipeline health, predict outcomes, and identify the levers that unlock sustainable growth.

Key Responsibilities

• Model the Business: Build forecasting and propensity models for pipeline generation, conversion rates, and revenue projections.
• Optimize the Sales Funnel: Analyze lead scoring, opportunity progression, and deal velocity to recommend improvements in acquisition, qualification, and close rates.
• Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of pricing, incentives, and campaign initiatives.
• Advanced Analytics for GTM: Apply machine learning and statistical techniques to segment accounts, predict churn/expansion, and identify high-value prospects.
• Cross-Functional Partnership: Work closely with Sales, Marketing, RevOps, and Product to influence GTM strategy and ensure data-driven decisions.
• Data Infrastructure Collaboration: Partner with Analytics Engineering to define data requirements, ensure data quality, and enable self-serve reporting.
• Strategic Insights: Present findings to executive leadership, translating complex analyses into actionable recommendations.

About You

• Experience: 6+ years in data science or advanced analytics roles, with significant time spent in B2B SaaS or developer tools environments.
• Technical Depth: Expert in SQL and proficient in Python or R for statistical modeling, forecasting, and machine learning.
• Domain Knowledge: Strong understanding of sales analytics, revenue operations, and product-led growth (PLG) motions.
• Analytical Rigor: Skilled in experimentation design, causal inference, and building predictive models that influence GTM strategy.
• Communication: Exceptional ability to tell a clear story with data and influence senior stakeholders across technical and business teams.
• Business Impact: Proven record of driving measurable improvements in pipeline efficiency, conversion rates, or revenue outcomes.