About the Role

We are looking for an experienced Staff Data Scientist to support Slack's Go-to-Market (GTM) organization. In this role, you will partner with Sales Strategy, Sales Programs, Product, Finance, and Data teams to uncover opportunities that accelerate growth, improve customer outcomes, and shape GTM strategy through data.

You will work on some of Slack's highest-impact business questions, applying advanced analytics, experimentation, and statistical methods to understand customer behavior, evaluate strategic initiatives, and optimize GTM performance. As Slack continues to invest in AI-powered selling and customer intelligence, you will help define the analytical frameworks, predictive models, and measurement systems that enable smarter decisions at scale.

You will collaborate closely with Engineers, Business Leaders, and Researchers to identify opportunities, influence strategic direction, and build a culture of evidence-based decision making.

Slack has a positive, diverse, and supportive culture. We look for people who are curious, inventive, and strive to improve every day. In our work together, we aim to be smart, humble, hardworking, and, above all, collaborative. If this sounds like a great fit, we'd love to hear from you.

What You Will Be Doing

• Partner with GTM leadership to identify strategic opportunities, evaluate business performance, and influence key business decisions.

• Apply statistical methods, experimentation, and advanced analytics to understand customer behavior, sales performance, and drivers of business growth.

• Develop predictive models, segmentation frameworks, and forecasting methodologies that improve GTM planning and execution.

• Design measurement strategies and success metrics to evaluate products, programs, and strategic initiatives.

• Conduct deep-dive analyses to identify opportunities for revenue growth, customer adoption, operational efficiency, and field productivity.

• Build scalable analytical frameworks that uncover trends, quantify business impact, and support executive decision making.

• Partner with Data Engineering to develop trusted datasets and scalable analytical foundations that enable advanced modeling and experimentation.

• Collaborate with Product and Sales Strategy to develop intelligence solutions that connect account health, product usage, customer engagement, and seller actions into actionable recommendations.

• Translate complex analyses into compelling narratives, executive presentations, dashboards, and written recommendations tailored to both technical and non-technical audiences.

• Champion evidence-based decision making by improving access to trusted metrics, analytical methodologies, and strategic insights across the GTM organization.

What You Should Have

• 6+ years of industry experience applying data science, statistics, or quantitative analysis to solve complex business problems.

• 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, predictive modeling, 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.

• Experience partnering with Product, Sales, Finance, or other GTM organizations to influence strategic decisions.

• Bachelor's degree in Computer Science, Statistics, Economics, Mathematics, Engineering, or another quantitative field, or equivalent practical experience.

Preferred Qualifications

• Master's degree or PhD in Statistics, Computer Science, Economics, Mathematics, Operations Research, or a related quantitative discipline.

• Experience supporting Sales, Marketing, Customer Success, Finance, or other Go-to-Market organizations through advanced analytics.

• Expertise in experimental design, A/B testing, causal inference, forecasting, or machine learning.

• Experience developing production-quality analytical models and partnering with engineering teams to operationalize data science solutions.

• Deep understanding of GTM operating models and experience collaborating with Sales Strategy and Sales Programs teams.

• Demonstrated ability to independently define ambiguous business problems, develop rigorous analytical approaches, and influence executive-level strategy.

• Experience applying AI and machine learning techniques to improve business decision making, operational efficiency, or customer experiences.