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# Decision Scientist Senior

- **Company:** Salesforce.com, Inc.
- **Location:** Seattle, WA, United States
- **Experience:** Expert
- **Salary:** $148,500.0 - $223,900.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software Quality, Data Mining, Data Systems, Decision Support Systems, Python (Programming Language), Systems Integration, Feature Engineering, Sql Optimization, Large Language Models, Multi-Agent Systems, Information Technology, Statistics Packages, Data Analytics, Virtual Agents, Data Pipelines
- **Published:** August 4, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/87927157/1

## About the Role

* Proven Experience: 5+ years of hands-on experience in data science, decision science, or quantitative analytics, with a proven track record of delivering insights and models that influence product strategy.
 * Agentic AI & Automation: Practical experience building agentic workflows, integrating LLMs, or automating complex data pipelines using modern AI frameworks. You actively leverage AI to build smarter, faster analytics systems.
 * Technical Proficiency: Strong proficiency in statistical programming languages (Python or R) and modern data science tools, alongside advanced SQL skills for complex data extraction and feature engineering.
 * Quantitative Foundation: Master's degree (or Bachelor's with equivalent practical experience) in a quantitative discipline (e.g., Computer Science, Engineering, Economics, Statistics, or Applied Mathematics).
 * Communication & Collaboration: Excellent written and verbal communication skills, with a demonstrated ability to synthesize technical details for product and business partners.
 * Ownership & Drive: A strong bias for action and personal accountability, comfortable navigating ambiguity and working independently in a dynamic, matrixed environment.

## Description

* Decision Support & Strategic Guidance: 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. Deliver clear recommendations that drive product and business decisions.
 * Stakeholder Partnership: Partner directly with product managers, engineering leads, and cross-functional stakeholders to translate complex analytical findings into clear, actionable business recommendations.
 * Agentic Systems & AI Lifecycle: Architect, evaluate and govern autonomous AI agents to automate complex data science tasks, accelerating our analytical throughput and decision systems. Incorporate AI solutions into daily analytical workflows to drive faster time-to-insight.
 * Roadmap Execution: Contribute technical expertise to the AgentExchange product analytics roadmap, taking end-to-end ownership of project execution and delivery.
 * Metrics & Insights: Define, build, and track key performance indicators to monitor AgentExchange adoption, feature health, and long-term user engagement.
 * Peer Leadership: Practice and promote high standards for technical rigor, code quality, and documentation, providing informal mentorship to peers across the Cloud Analytics organization.


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