Lead Decision Scientist

Benefits

Parental leave

26 weeks From the posting source checked Jun 20, 2026

Non-birth-parent leave

12 weeks From the posting source checked Jun 20, 2026

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Source-linked checked May 7, 2026

Salary

$172K-$260K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

93% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Lead Decision Scientist Washington - Seattle; Illinois - Chicago; Washington - Bellevue 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. What We're Looking For Required Qualifications 8+ years of experience in a quantitative role, with a proven track record deploying causal models or experimental frameworks in

Read the full description at careers.salesforce.com. FewerJobs shows a preview and links to the original posting.