Lead Decision Scientist

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword— it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. 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. Required Qualifications 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. Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications—without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education. 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 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. #J-18808-Ljbffr