Senior Decision Scientist
Company websitesalesforce.com (Salesforce, opens in new tab)
Base salary From $172,500
Employer-published annual base salary, USD. Advertised base range in United States
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationUnited States
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
DataJob Details
About Salesforce
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.
The Experience
Data Solutions is the force that propels Salesforce into the AI era, informing—through trusted data and artificial intelligence—the path forward to be smarter in every dimension. Delivering everything from financial forecasting and customer health to adoption insights and curated data, Data Solutions serves as the unbiased partner to every data trailblazer across Salesforce.
As part of this organization, Product & Success Analytics operates as the strategic product analytics engine, partnering directly with CSG leadership to drive high-stakes decision-making through rigorous metrics and insights. Embedded directly within Success Analytics, this role serves as a strategic partner to product, engineering, and data leaders - co-building the foundational data architectures, key performance metrics, and AI-driven capabilities needed to propel product adoption.
The Senior Decision Scientist will serve as a lead technical authority on the team, leveraging advanced data science, statistical modeling, and quantitative analytics to power mission-critical operational systems. In this role, you will own the modeling, data architecture, and statistical rigor behind product Adoption telemetry - systems that directly govern performance metrics and compensation target-setting across the organization for Sales & CSG.
Working in tight partnership with Product Leadership, senior executive stakeholders, and cross-functional engineering teams, you will apply rigorous analytics to architect next-generation compensation and adoption metrics, drive automated data frameworks to scale M&A signal ingestion across incoming acquisitions, and enforce top-tier data trust and SLA reliability across underlying analytics pipelines.
What You'll Actually Be Doing
- Requirements & Data Discovery: Partner directly with business stakeholders to translate complex compensation strategies and operational goals into precise quantitative requirements and data definitions.
- Impact Analysis & Historical Modeling: Perform deep-dive data exploration, scenario modeling, and historical backfills on underlying usage and telemetry tables to quantify the impact of proposed metric changes across Sales & CSG prior to rollout.
- End-to-End Metric Build & Validation: Design, build, and statistically validate scoring logic and underlying data pipelines, ensuring calculations are robust, audit-ready, and resilient against edge cases.
- M&A Signal Integration & Scalable Data Frameworks: Serve as the lead Decision Scientist for designing and executing M&A data integration frameworks, transitioning signal ingestion from a manual "pull" model to an automated "push" model to drop onboarding cycle times from weeks to days.
- Strategic Advisory & Executive Alignment: Apply rigorous quantitative methods—including experimentation, causal inference, and tradeoff analysis—to inform product initiatives, advise senior leadership, and translate complex insights into clear business strategies.
- Agentic Systems & AI Lifecycle: Architect, evaluate, and govern autonomous AI agents to automate complex data science tasks, incorporating AI solutions into daily analytical workflows to accelerate time-to-insight.
- Data Integrity, Reliability & SLA Optimization: Own analytical health, automated anomaly detection, and root-cause data investigations for product adoption telemetry and underlying tables, dramatically reducing SLAs for bug resolution during critical compensation cycles.
- Technical Leadership & Mentorship: Elevate the team's technical bar by establishing best practices for statistical rigor and feature engineering while mentoring peers across Success Analytics and Data Solutions.
You're Our Person If...
- Proven Experience: 8+ years of hands-on experience in Data Science, Decision Science, Advanced Analytics, or Quantitative Product Analysis in enterprise SaaS environments, with a proven track record of deploying models that move business needles.
- Agentic AI & Systems Engineering: Demonstrated experience architecting agentic workflows, orchestrating LLMs, or building automated, self-correcting data science systems. You don't just use AI; you build systems that leverage it.
- Technical Mastery: High proficiency in statistical programming languages (Python or R) and modern data science stacks, along with exceptional SQL skills for complex feature engineering and database performance tuning.
- Quantitative Foundation: Master's degree or MBA in a highly quantitative discipline (e.g., Computer Science, Engineering, Economics, Statistics, or Applied Mathematics).
- Domain & Business Acumen: Proven track record applying data science to business metrics, health scoring algorithms, or incentive compensation structures across Sales and Customer Success organizations.
- Executive Presence: Exceptional communication skills with the ability to build trust with C-suite executives, align technical teams, and tell a compelling story with data.
- Entrepreneurial Execution: A "get-it-done" mindset with a strong bias for action, comfortable operating with high autonomy in a global, matrixed environment.
Unleash Your Potential
When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
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. Know your rights: workplace discrimination is illegal. 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 the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.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. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,800 annually.

The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.Source: Salesforce on Workday · View original posting (opens in new tab)
Pay in context
This role's base floor ($172,500) is above 75% of the 320 Science & Research roles in California listed on this site; 1 other lists the same floor. Their median floor is $143,200; the middle half runs from $120,000 to $172,100.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.
This listingSenior Decision ScientistFrom $172,500
Technical Program Management Director, Digital MarketingFrom $171,200
Life Sciences Product Liaison DirectorFrom $171,200
Staff Technical Program Manager, GrowthFrom $171,200
Director, Qualified Success ArchitectureFrom $171,200
Director, Marketing Cloud Architecture$171,200 to $273,000
Director, AI Labs ScoutsFrom $171,200
Chart as a table
| Role | Published base |
|---|---|
| Senior Decision Scientist (this listing) | From $172,500 |
| Technical Program Management Director, Digital Marketing | From $171,200 |
| Life Sciences Product Liaison Director | From $171,200 |
| Staff Technical Program Manager, Growth | From $171,200 |
| Director, Qualified Success Architecture | From $171,200 |
| Director, Marketing Cloud Architecture | $171,200 - $273,000 |
| Director, AI Labs Scouts | From $171,200 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-11-03
Where this pay comes from
Location as the employer wrote it: US (regional bands)
ble 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. In select cities within the San Francisco and New
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
