Drimva

Salesforce

Staff / Principal Product Data Scientist - Slack

$172K–$345K

California - San Francisco +3 · Office Tech-Flexible · Principal · Full-time · Posted Sep 17, 2026

Location
California - San Francisco
New York - New York
Georgia - Atlanta
Washington - Seattle
Experience
5+ years of experience in product data science in related tech industries.
Education
Related degree required; a BS degree in a quantitative field is given as an example. An advanced degree (MS, PhD) is a strong plus.

About the job

Leads product data science for Slack, using analytics and experimentation to shape product strategy, measure product health, and develop an AI-enabled data self-service platform.

What you'll do

  • Partner with product stakeholders to identify opportunities, prioritize roadmaps, and support evidence-based product decisions.
  • Evaluate drivers of product adoption and build success metrics, reporting, and canonical data sources.
  • Contribute to the design and implementation of Slack’s agentic data delivery platform.

What they ask for

  • 5+ years of product data science experience in related tech industries.
  • Advanced SQL proficiency and proficiency in at least one data science programming language, such as Python, R, or Scala.
  • Strong foundation in statistics, experimentation, causal inference, ML, and analytical problem-solving; experience with large-scale distributed data platforms.
  • Related degree required; BS in a quantitative field is given as an example.

Nice to have

  • Knowledge of workflow orchestration tools such as Apache Airflow.
  • Advanced degree (MS, PhD).

Pay

USD $172,500 - $313,700 annually (base salary); USD $207,800 - $344,700 annually (base salary)

Tools

SQL, Python, R, Scala, Apache Airflow, Spark, Presto, Hive

AI focus

Design and develop Slack’s agentic data delivery platform to support data self-service in an AI and agentic context. Salesforce also states it uses AI tools to help assess candidate resumes and qualifications; humans make hiring decisions.

Model-written summary · the original posting is authoritative

First seen Oct 10, 2026 · Last verified Nov 5, 2026 (UTC)