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Staff Product Data Scientist - Slack

Salesforce - California - San Francisco; Washington - Seattle; Georgia - Atlanta; Washington - Bellevue

Posted Apr 17, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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Learning budget
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Verification
Source-linked last checked May 7, 2026
Salary
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401(k) match
Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked May 7, 2026.

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Schedule

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Weekend work
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Application

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About this role

Staff Product Data Scientist - Slack California - San Francisco; Washington - Seattle; Georgia - Atlanta; Washington - Bellevue We are looking for a seasoned Data Science Expert to help build a world-class data science analytics platform that supports and scales data-driven product decision-making. As a Staff Product Data Scientist, you will work closely with cross-functional partners to proactively define the product landscape, derive insights from data, communicate key findings to product executives, and directly contribute to product strategy building and implementation. You'll partner with Product, Design, and Engineering (PDE) to contribute directly to product development-shaping what we build, how we measure success, and when/how we iterate and improve. At Slack, we foster a positive, diverse, and supportive culture. We look for people who are curious, bold, and eager to improve every day. Our team values being smart, humble, hardworking, and above all, collaborative. What you will be doing Apply advanced data science techniques to analyze Slack product usage patterns, identifying what's working, what's not, and opportunities for improvement. Conduct evidence-based evaluations to determine key drivers of Slack's product growth. Define and report key success metrics, effectively communicating insights to Slack and Salesforce leadership to enable executive level decision making and follow-ups. Synthesize insights across different product areas and business outcomes, identifying correlations and causal relationships that drive success. Serve as a domain expert in product data science, guiding best practices and advancing data science methodologies and operations. Champion evidence-based decision-making, making data and insights accessible and scalable for stakeholders

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