Product Director - Machine Learning

Salesforce•Austin, TX

About The Position

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. Department Overview The Analytics Tools Team within Salesforce’s Customer Success Group (CSG) helps customers unlock the full value of their Salesforce investments through data-driven insights. We build and manage three critical products that provide a comprehensive view of the customer experience: Customer Success Score, which delivers actionable recommendations to measure and improve success; Proactive Monitoring, which offers 24/7 automated alerts to detect and resolve issues early; and Attrition Risk Insights, an ML-powered solution that identifies churn risk and its root causes so teams can take timely, targeted action. Role Overview As the Machine Learning Product Director for Attrition Risk Insights , you own the end-to-end Machine Learning strategy behind the company’s source of truth for customer risk. Attrition Risk Insights uses Machine Learning at its core to identify churn risk and its root causes so teams can take timely, targeted action. In close partnership with the Data Science team, you will co-own the modeling roadmap, experimentation strategy, and model performance—ensuring accuracy, explainability, and measurable business impact. You will serve as the bridge between the Data Science team and product consumers, translating business use cases and customer needs into clear technical product requirements. Together, you will empower Customer Success, Renewals, and Sales to proactively mitigate churn risk with Attrition Risk Insights. Why Join the Salesforce Customer Success Group? Join us at a pivotal moment where reducing customer attrition is an executive-level priority and Attrition Risk Insights serves as the company’s definitive source of truth for customer risk. Having launched in February 2026, the product is now in its critical adoption phase—creating a rare opportunity to shape how machine learning is trusted, embedded into workflows, and translated into measurable retention impact. Our Values At Salesforce, Trust, Customer Success, Innovation, Equality and Sustainability are more than just words. They are our core values, guiding every decision and every interaction. Join Salesforce and be part of a company dedicated to making technology accessible to all and helping create a future of greater opportunity. 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.

Requirements

Strategic, Analytical, and Collaborative Skills: Strong strategic thinker with an ability to leverage advanced data analysis and predictive modeling to drive customer engagement and product improvement. Skilled at collaborating and influencing across all levels of an organization, especially in driving alignment with executive and senior leadership.
Product Management Leadership: Minimum of 10 years of product management experience with demonstrated leadership in highly matrixed, cross-functional environments. Must have a proven track record of successfully scaling products to support hundreds of thousands of customers.
Machine Learning-focused Product Management: 5+ years of experience collaborating with Data Science or Machine Learning model development teams.
Educational Background: Bachelor’s degree in Business, Engineering, Marketing, Data Science, or a related field; MBA or equivalent experience preferred.

Responsibilities

Own ML Strategy & Performance: Define the ML roadmap, success metrics (technical and business), experimentation plans, and model iteration lifecycle from deployment through monitoring and retraining.
Operationalize ML Insights: Embed risk predictions, confidence signals, and explainability into field workflows to drive clear, actionable mitigation steps.
Drive Trust & Continuous Improvement: Establish feedback loops, monitor drift and bias, and continuously improve model accuracy, calibration, and adoption.
Lead Cross-Functional Alignment: Serve as the bridge between Data Science, Engineering, and Field teams to ensure scalable, responsible, and high-impact ML execution.