Lead Decision Scientist

Salesforce Salesforce · Enterprise · Seattle, WA +2

Salesforce is seeking a Lead Decision Scientist to build evaluation frameworks for AI systems, focusing on agentic workflows and LLM-as-a-judge metrics. The role involves designing and analyzing experiments, setting statistical standards, and influencing strategy through data-driven storytelling. This senior individual contributor role requires expertise in causal inference and production deployment of models, with a focus on AI reliability and impact in an enterprise AI CRM context.

What you'd actually do

  1. Build evaluation frameworks for AI systems
  2. Solve complex attribution problems
  3. Lead experimental design
  4. Set the statistical standard
  5. Influence strategy through storytelling

Skills

Required

  • 8+ years of experience in a quantitative role
  • deploying causal models or experimental frameworks in production environments
  • causal inference
  • high-dimensional regression
  • time-series analysis
  • forecasting
  • Python
  • R
  • PyData stack (Pandas, NumPy, SciPy, Statsmodels, Scikit-learn)
  • Expert-level SQL skills
  • cloud data warehouses (Snowflake, BigQuery)
  • communicate statistical findings clearly to non-technical executive audiences

Nice to have

  • LLM evaluation metrics
  • statistical challenges of non-deterministic AI systems
  • agentic or AI product teams
  • experimental economics
  • operations research

What the JD emphasized

  • proven track record deploying causal models or experimental frameworks in production environments
  • Deep expertise in causal inference
  • non-deterministic AI systems

Other signals

  • AI CRM
  • agentic era
  • AI reliability and impact
  • evaluation frameworks for AI systems
  • agentic workflows
  • LLM-as-a-judge metrics
  • non-deterministic outputs
  • experimental design
  • statistical standard
  • executive visibility