Staff / Principal Product Data Scientist - Slack

Leadout Capital; San Francisco (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Slack is hiring Staff & Principal Product Data Scientists to build a world-class data ecosystem that supports data-driven product decision-making. You will partner with PDE and GTM teams to shape product development, measure success, and iterate.

You will design and develop Slack's agentic data delivery platform, connecting data backend, metrics foundations, and insights analyses to enable true data self-serve capabilities in an AI context.

Qualifications

• 5+ years of product data science experience in tech.
• Proven record of using data to influence product decisions.
• Strong SQL and at least one DS language.
• Solid foundation in statistics, experimentation, and ML.
• Experience with large-scale data tech like Spark/Presto/Hive.
• Excellent communication with executives.
• BS in quantitative field; MS/PhD a strong plus.

Responsibilities

• Establish partnerships with product stakeholders to prioritize roadmaps.
• Evangelize evidence-based decision-making and data accessibility.
• Evaluate drivers for increased product adoption.
• Build success metric frameworks and self-serve reporting.
• Prototype data models with Data Engineering to create canonical sources.
• Contribute to agentic data delivery platform design and implementation.
• Identify opportunities to improve user experiences and business value.
• Collaborate with Product Researchers to align roadmaps.

Skills

SQL proficiency

Programming (Python/R/Scala)

Statistics and causal inference

Data storytelling to executives

Cross-functional collaboration

Education

BS in quantitative field (CS, Econ, Physics)

MS/PhD a strong plus

Tools

Apache Airflow

Spark

Presto

Hive/Hadoop

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.

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:

• 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.