Data Science Principal

Salesforce · California - San Francisco · Georgia - Atlanta · Washington - Seattle

hybridfull-time10+ years

posted 2d

Skills: Salesforce, CRM

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 Data 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. Title: Principal Data Scientist, Platform Monetization We are hiring a Principal Data Scientist to lead the data efforts to form Slack monetization strategy and execution from the agentic platform point of view. The Platform ecosystem is a critical component of Slack's strategy to become the place where work happens. It enables users to truly customize Slack and integrate their everyday tools to streamline and speed up work. At the same time, this domain connects with corporate sales and business and strategic customer strategy and directly impacts the company's topline performance. In this leadership role, you will work closely with the Platform product organization to understand and improve the product experience of app developers and users. As Slack builds out its next generation of Platform capabilities, you'll lead the efforts on unearthing insights and building a complete picture of what users build and how they engage with agents and with each other on the Slack platform. At the same time, you will partner closely with go-to-market (GTM) teams to answer Slack's highest-impact business questions. Slack has a positive, diverse, and supportive culture—we look for people who are curious, inventive, and work to be a little better every single day. In our work together we aim to be smart, humble, hardworking and, above all, collaborative. If this sounds like a good fit for you, we'd love to hear from you. What you'll be doing: Establish strong partnership with product and business stakeholders in identifying opportunities, prioritize roadmaps, define and implement execution excellence, and coach and mentor team members for execution excellence Apply statistical methods, experimentation, segmentation frameworks, and forecasting methodologies to understand customer behavior, GTM performance, and drivers of growth Design measurement strategies and success metrics to evaluate products, programs, and strategic initiatives Frame and deliver deep-dive analyses to identify opportunities for revenue & product growth, customer adoption, and smooth user journeys Partner with Data Engineering to develop trusted datasets and scalable analytical foundations that enable advanced modeling and experimentation Set a compelling vision and prioritize work based on product strategies and overall business goals Partner closely with product researchers and business strategy partners, align roadmaps and collaborate on projects to influence topline decision making What you should have: 7+ years of experience in product data science in related tech industries; 2+ years experience in a product DS tech lead or managerial role a strong plus A consistent record of using data to drive product teams to achieve ambitious goals and influencing company-level outcomes Advanced proficiency in SQL and at least one programming language for data science, such as Python, R, or Scala. Knowledge of workflow orchestration tools like Apache Airflow is highly desirable Strong foundation in statistics, experimentation, causal inference, predictive modeling, and analytical problem solving Experience working with large-scale data technologies such as Spark, Presto, Hive, Ha