Lead Decision Scientist
Role details
Job location
Tech stack
Job description
Salesforce's Data & Analytics organization is looking for a Decision Scientist who thrives at the intersection of AI, automation, and rigorous quantitative analysis. In this role, you'll build the measurement frameworks that define how we evaluate agentic systems, run high-stakes experiments, and directly shape product and business strategy through data-driven storytelling. This is a senior individual contributor role with real executive visibility and the opportunity to pioneer how an enterprise thinks about AI reliability and impact. What You'll Do
- Build evaluation frameworks for AI systems - Design and scale methodologies to assess the performance, reasoning quality, and reliability of agentic workflows, including LLM-as-a-judge metrics and approaches tailored to non-deterministic outputs.
- Solve complex attribution problems - Develop causal inference models that distinguish true incremental gains from organic trends, using the right modeling technique for each problem.
- Lead experimental design - Own the design and analysis of sophisticated experiments - from multivariate and switchback designs to quasi-experimental methods for environments where randomization isn't feasible.
- Set the statistical standard - Serve as the department's final reviewer for statistical methodology, ensuring rigor is appropriately calibrated to the stakes of each analysis.
- Influence strategy through storytelling - Translate complex quantitative findings into clear, actionable narratives for executive leadership, shaping both the product roadmap and long-term business direction.
Requirements
- 8+ years of experience in a quantitative role, with a proven track record deploying causal models or experimental frameworks in production environments
- Deep expertise in causal inference, high-dimensional regression, time-series analysis, and forecasting
- Strong proficiency in Python or R (PyData stack: Pandas, NumPy, SciPy, Statsmodels, Scikit-learn)
- Expert-level SQL skills for complex data extraction, feature engineering, and query performance tuning in cloud data warehouses (e.g., Snowflake, BigQuery)
- Demonstrated ability to communicate statistical findings clearly to non-technical executive audiences
Preferred Qualifications
- Familiarity with LLM evaluation metrics and the unique statistical challenges of non-deterministic AI systems
- Experience working on or alongside agentic or AI product teams
- Background in experimental economics or operations research
Education
A related technical degree required.
Benefits & conditions
In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com. At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $172,500 - $260,100 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.
