Decision Scientist Senior

Salesforce Salesforce · Enterprise · San Francisco, CA +1

Senior Decision Scientist role at Salesforce focused on building and evaluating autonomous AI agents to automate data science tasks and accelerate analytical throughput. The role involves partnering with product and engineering teams to drive product decisions using quantitative methods and AI solutions, and defining key performance indicators for AI agent adoption and effectiveness.

What you'd actually do

  1. Architect, evaluate and govern autonomous AI agents to automate complex data science tasks, accelerating our analytical throughput and decision systems.
  2. Incorporate AI solutions into daily analytical workflows to drive faster time-to-insight.
  3. Define, build, and track key performance indicators to monitor AgentExchange adoption, feature health, and long-term user engagement.
  4. 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.
  5. Partner directly with product managers, engineering leads, and cross-functional stakeholders to translate complex analytical findings into clear, actionable business recommendations.

Skills

Required

  • 5+ years of hands-on experience in data science, decision science, or quantitative analytics
  • Proven track record of delivering insights and models that influence product strategy
  • Practical experience building agentic workflows, integrating LLMs, or automating complex data pipelines using modern AI frameworks
  • Actively leverage AI to build smarter, faster analytics systems
  • Strong proficiency in statistical programming languages (Python or R)
  • Advanced SQL skills for complex data extraction and feature engineering
  • Master’s degree (or Bachelor’s with equivalent practical experience) in a quantitative discipline (e.g., Computer Science, Engineering, Economics, Statistics, or Applied Mathematics)
  • Excellent written and verbal communication skills
  • Demonstrated ability to synthesize technical details for product and business partners
  • A strong bias for action and personal accountability
  • Comfortable navigating ambiguity and working independently in a dynamic, matrixed environment

What the JD emphasized

  • autonomous AI agents
  • automate complex data science tasks
  • Agentic Systems & AI Lifecycle
  • agentic workflows
  • integrating LLMs
  • automating complex data pipelines
  • modern AI frameworks
  • AI solutions
  • AI agents

Other signals

  • architecting AI agents
  • automating data science tasks
  • integrating LLMs
  • building agentic workflows