Staff/Principal Product Data Scientist: AI-Driven Insights

100 Salesforce, Inc.; San Francisco (CA); On-site; USD 173,000 - 314,000; Full time

Benefits offered by this job

401(k) matching

Employee stock purchase program

Health, dental, vision insurance

Job summary

Salesforce is seeking Staff & Principal Product Data Scientists to shape data-driven product decisions and build Slack’s agentic data delivery platform. Collaborate with PDE and GTM to align roadmaps and deliver measurable product improvements.

You will partner with stakeholders to define the product landscape, develop self-serve insights, and drive adoption through robust metrics and analytics capabilities.

Qualifications

• 5+ years of product data science experience in tech industries.
• Advanced SQL and at least one DS language (Python/R/Scala).
• Experience with large-scale data technologies (Spark, Presto, Hive, Hadoop).
• Ability to communicate findings clearly to execs and cross-functional teams.

Responsibilities

• Establish partnerships with product stakeholders to identify opportunities and roadmap.
• Evangelize data-driven decisions and enable self-serve data.
• Evaluate drivers for adoption of Slack product capabilities.
• Build metrics frameworks and self-serve reporting for product health.
• Design and implement data delivery platforms.
• Identify opportunities to improve user experiences and business value.
• Collaborate with product researchers to align roadmaps.

Skills

5+ years of data science

SQL

Python/R/Scala

Airflow

Statistics/Experimentation

Large-scale data tech

Communication to execs

BS in quantitative field

MS/PhD a plus

Education

B.S. in Computer Science/Economics/Physics

MS/PhD preferred

Tools

Apache Airflow

Spark/Presto/Hadoop

Job description

Salesforce is seeking Staff & Principal Product Data Scientists to shape data-driven product decisions and build Slack’s agentic data delivery platform. Collaborate with PDE and GTM to align roadmaps and deliver measurable product improvements.

You will partner with stakeholders to define the product landscape, develop self-serve insights, and drive adoption through robust metrics and analytics capabilities.