Staff Business Data Scientist - Slack

Job Description

Slack is looking for a Staff Data Scientist to join our Business Data Science team. In this role, you will be responsible for leveraging data to help drive the growth and success of the Slack Business Unit. The ideal candidate is an effective communicator, has strong analytical thinking, can operate independently with minimal guidance, has a growth mindset, collaborates effectively with others, and biases towards action and impact.

The Business Data Science team is focused on helping executives and other key decision makers across the company make better business decisions using data. We partner closely with Data Engineering, Business Strategy & Operations, Go-To-Market, and Product, Design, and Engineering (PDE) teams to identify growth opportunities, forecast performance, and deliver impactful analyses and models.

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, why not say hello?

What you will be doing

• Partner with Slack Growth teams to understand the drivers of our business and accelerate growth
• Synthesize insights into crisp narratives and present to senior leadership
• Develop frameworks for identifying patterns/trends in customer behavior
• Empower others to be self-sufficient in data by building self-service tools and reports to drive awareness and understanding of key metrics
• Work with our Data Engineering teams to build core data models that power operational and exploratory data analyses

What you should have

• 5+ years of professional industry experience doing quantitative analysis
• A related technical degree required. A BS degree in a quantitative field (e.g., Computer Science, Economics, Physics); an advanced degree (MS, PhD) is a strong plus.
• Advanced proficiency in SQL and at least one programming language for data science, such as Python, R, or Scala.
• Strong foundation in statistics, experimentation, causal inference, ML, and analytical problem-solving.
• Proven ability to communicate complex analytical findings to influence stakeholders and strategic decision making.

Preferred Experience

• Designing, running, and analyzing growth focused experiments
• Applying analytics to uncover potential growth opportunities
• Successful collaboration with Marketing, Growth, Go-To-Market, and/or Lifecycle teams
• Experience using AI / agentic tools for analysis, and building reusable analytical tools