Senior Data Scientist
7 days ago
Senior Data Scientist - Sales Analytics
Location: San Francisco (Hybrid)
Salary: $200-250k base + RSUs
This dynamic Series E AI SaaS company is on a mission to transform how engineering teams develop and launch applications. We are seeking a talented Senior Data Scientist to spearhead Sales and Go-to-Market (GTM) analytics, utilizing advanced modeling and experimentation to drive revenue growth and enhance the entire sales pipeline.
About the Role
In this pivotal role, you will leverage statistical modeling, experimentation, and sophisticated analytics to shape strategies and drive decisions within our revenue organization. Your expertise will enable leadership to gain vital insights into pipeline health, forecast outcomes, and pinpoint opportunities for sustainable growth.
Key Responsibilities
- Model the Business: Develop forecasting and propensity models to enhance pipeline generation, conversion rates, and revenue forecasts.
- Optimize the Sales Funnel: Assess lead scoring, opportunity progression, and deal velocity to propose enhancements in acquisition, qualification, and closing rates.
- Experimentation & Causal Analysis: Craft and analyze experiments (A/B tests, uplift modeling) to evaluate the effects of pricing, incentives, and campaign initiatives.
- Advanced Analytics for GTM: Implement machine learning and statistical methods to segment accounts, predict churn/expansion, and identify high-value targets.
- Cross-Functional Partnership: Collaborate closely with Sales, Marketing, RevOps, and Product teams to shape GTM strategies and promote data-driven decision-making.
- Data Infrastructure Collaboration: Partner with Analytics Engineering to specify data needs, ensure data accuracy, and facilitate self-service reporting.
- Strategic Insights: Communicate findings to executive leadership, translating complex analyses into practical recommendations.
About You
- Experience: 6+ years in data science or advanced analytics, with a strong background in B2B SaaS or developer tool environments.
- Technical Depth: Mastery of SQL and proficient in Python or R for statistical analysis, forecasting, and machine learning applications.
- Domain Knowledge: In-depth understanding of sales analytics, revenue operations, and product-led growth strategies.
- Analytical Rigor: Expertise in experimental design, causal inference, and the creation of predictive models that drive GTM strategies.
- Communication: Outstanding ability to present data-driven insights compellingly and influence senior stakeholders across technical and business domains.
- Business Impact: A proven track record of enhancing pipeline efficiency, increasing conversion rates, or generating revenue results.
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