Full Job Description
We are hiring Staff & Principal Product Data Scientists to help build a world-class data ecosystem that supports and scales data-driven product decision-making at Slack.
As Staff & Principal Product Data Scientists, you will work closely with cross-functional partners to define the product landscape, derive actionable insights, and directly shape product strategy. You'll partner with Product, Design, and Engineering (PDE), as well as Go-To-Market (GTM) teams, to contribute directly to product development-shaping what we build, how we measure success, and how we iterate.
You will also play a pivotal role in designing and developing Slack's agentic data delivery platform. By connecting the dots across our data backend, metrics foundations, and insights analyses, you will help us achieve true data self-serve capabilities within an AI and agentic context.
What you will be doing:
• Establish strong partnerships with product stakeholders to identify opportunities, prioritize roadmaps, and implement execution excellence.
• Evangelize evidence-based decision-making by partnering with key leaders and driving the general accessibility of data and insights.
• Perform evidence-based evaluations of the most important drivers for increased adoption of Slack product capabilities.
• Build key success metric frameworks and self-serve reporting to monitor Slack product health.
• Prototype foundational data models and partner with Data Engineering functions to elevate these into canonical sources of truth.
• Contribute to the design and implementation of Slack's agentic data delivery platform.
• Quantitatively identify potential product opportunities to improve user experiences and unlock business value.
• Partner closely with Product Researchers to align roadmaps and collaborate on projects to answer complex questions.
What you should have:
• 5+ years of experience in product data science in related tech industries.
• A consistent record of using data to drive product teams to achieve ambitious goals and influence 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, ML, and analytical problem-solving.
• Experience working with large-scale data technologies such as Spark, Presto, Hive, Hadoop, or similar distributed data platforms.
• Proven ability to communicate complex analytical findings clearly to executive and cross-functional audiences.
• A related degree required. A BS degree in a quantitative field (e.g., Computer Science, Economics, Physics); an advanced degree (MS, PhD) is a strong plus.
