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Salesforce

Data Science Architect - AI/ML & Decision Intelligence

Reposted Yesterday
In-Office or Remote
6 Locations
117K-194K Annually
Mid level
In-Office or Remote
6 Locations
117K-194K Annually
Mid level
The role involves managing ML modeling, overseeing data cloud integration, and strategic planning for AI/ML support in the Renewals team.
The summary above was generated by AI

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Job Category

Operations

Job 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.

About the Role
We're seeking an exceptional Data Science Architect who specializes in building intelligent decision-making systems that drive measurable business outcomes. This role sits at the intersection of advanced analytics, machine learning, and enterprise AI, partnering with cross-functional teams to transform complex business problems into scalable, data-driven solutions.
What You'll Do
Build Predictive Models & Decision Intelligence Systems

  • Design and deploy end-to-end machine learning pipelines that predict business outcomes (e.g., renewal complexity, customer churn risk, revenue forecasting)
  • Apply predictive modeling, causal inference, and optimization to create decision policies that maximize business KPIs
  • Build ranking systems using advanced metrics (e.g., NDCG) to prioritize opportunities and optimize resource allocation

Drive Innovation in Agentic AI & Enterprise Intelligence

  • Define the architectural relationship between Agentic AI systems and Decision Intelligence layers
  • Design systems where AI agents execute tasks while Decision Intelligence systems determine which actions to take based on data-driven insights
  • Bridge the gap between natural language understanding and quantifiable business impact

Partner with Business Teams

  • Collaborate with renewal managers, sales operations, and customer success teams to understand business goals and translate them into analytical problems
  • Present complex technical concepts to non-technical stakeholders through intuitive visualizations and explainable model outputs
  • Iterate on solutions based on real-world feedback and changing business needs

Technical Excellence & Best Practices

  • Work with Einstein Notebooks, Python, and enterprise data platforms to build production-grade ML solutions
  • Troubleshoot complex data pipeline issues including S3 credential management and data access patterns
  • Create comprehensive documentation including model cards, evaluation reports, and deployment guides

Required Skills & Experience

  • 3+ years of experience in data science, machine learning, or related fields
  • Proficiency in Python and ML frameworks (scikit-learn, XGBoost, LightGBM, etc.)
  • Deep understanding of predictive modeling, classification, regression, and ranking algorithms
  • Experience with model interpretability techniques (SHAP, LIME, interpretable boosting machines)
  • Strong foundation in statistics, causal inference, and experimental design
  • Proven track record of deploying ML models to production that drive measurable business value

AI/ML Tools & Technologies

  • Languages: Python, SQL, R
  • ML Frameworks: scikit-learn, XGBoost, pandas, numpy
  • Platforms: Einstein Notebooks, Jupyter, Databricks, AWS/S3
  • Evaluation Metrics: NDCG, AUC-ROC, precision-recall, custom ranking metrics
  • Model Types: Gradient boosting, ensemble methods, interpretable ML models
  • Data Engineering: ETL pipelines, feature engineering, data quality validation

Desirable Experience

  • Background in Large Language Models (LLMs) and generative AI, including prompt engineering and understanding LLM capabilities versus traditional ML
  • Experience with Salesforce products (CRM, Marketing Cloud, Tableau) and enterprise data structures
  • Knowledge of optimization algorithms and operations research techniques
  • Experience with A/B testing and experimentation frameworks
  • Publications or presentations in data science/ML communities

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

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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 $117,400 - $177,600 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $140,900 - $193,700 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

Top Skills

Agentforce
Data Cloud
Databricks
Notebook Llm
Sales Cloud
Snowflake

Salesforce Burlington, Massachusetts, USA Office

5 Wall St, Burlington, MA, United States, 01803

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