Decision Scientist Lead - Cloud Analytics

Data Solutions is the force that propels Salesforce into the AI era, informing-through trusted data and artificial intelligence-the path forward to be smarter in every dimension. Delivering everything from financial forecasting and customer health to adoption insights and curated data, Data Solutions serves as the unbiased partner to every data trailblazer across Salesforce.

As part of this organization, Cloud Analytics operates as the strategic product analytics engine, partnering directly with cloud leadership to drive high-stakes decision-making through rigorous metrics and insights. Sitting within Cloud Analytics as a forward-deployed partner to AgentExchange, this role collaborates hand-in-hand with product, engineering, and data leadership to co-build the foundations, core metrics, strategic insights, and autonomous agents driving the product forward.

- Strategic Advisory: Apply rigorous quantitative and statistical methods, including experimentation, causal inference, tradeoff analysis, and modeling under uncertainty to inform product initiatives and diagnose complex business challenges. Serve as a trusted advisor and thought leader to senior T&P leadership (including the GM, COO, and Product Owners), translating complex analytical insights into clear, high-impact business strategies.

- Agentic Systems & AI Lifecycle: Architect, evaluate and govern autonomous AI agents to automate complex data science tasks, scaling our capability to deliver descriptive and prescriptive analytics at enterprise speed. Incorporate AI solutions into daily analytical workflows to drive faster time-to-insight.

- Stakeholder Partnership: Partner with cross-functional squads of analysts and engineers to diagnose complex business problems-applying rigorous quantitative methods and business context to provide clear descriptive analysis and actionable prescriptive solutions.

- Roadmap Ownership: Collaborate with cross-functional leaders to define the AgentExchange product analytics roadmap, prioritizing initiatives that drive maximum value and scale.

- Metrics & Growth: Define and track the critical product metrics required to accelerate AgentExchange adoption and long-term customer value.

- Technical Leadership & Mentorship: Elevate the team's technical bar by establishing best practices for statistical rigor and agentic engineering, while mentoring peers across the broader Cloud Analytics organization.

- Proven Experience: 8+ years of hands-on experience in data science, decision science, or advanced analytics, with a proven track record of deploying analytical models that move business needles.

- Agentic AI & Systems Engineering: Demonstrated experience architecting agentic workflows, orchestrating LLMs, or building automated, self-correcting data science systems. You don't just use AI; you build systems that leverage it.

- Technical Mastery: High proficiency in statistical programming languages (Python or R) and modern data science stacks, along with exceptional SQL skills for complex feature engineering and database performance tuning.

- Quantitative Foundation: Master's degree or MBA in a highly quantitative discipline (e.g., Computer Science, Engineering, Economics, Statistics, or Applied Mathematics).

- Executive Presence: Exceptional communication skills with the ability to build trust with C-suite executives, align technical teams, and tell a compelling story with data.

- Entrepreneurial Execution: A "get-it-done" mindset with a strong bias for action, comfortable operating with high autonomy in a global, matrixed environment.

The typical base salary range for this position is $172,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,800 annually.