Senior Data Scientist - GTM

Slack•Atlanta, GA

5d•$148,500 - $246,000

About The Position

Salesforce is seeking an experienced Senior Data Scientist to support Slack’s Go-to-Market (GTM) organization. The role partners with Sales Strategy, Sales Programs, Product, Finance, and Data teams to identify growth opportunities, improve customer outcomes, and shape GTM strategy through data. The successful candidate will apply advanced analytics, experimentation, and statistical methods to understand customer behavior, evaluate strategic initiatives, and optimize GTM performance. They will also help define analytical frameworks, predictive models, and measurement systems for AI-powered selling and customer intelligence, working closely with engineers, business leaders, and researchers to guide strategy and promote evidence-based decisions. The position focuses on strategic analysis and decision support across GTM. It includes developing models and measurement approaches, building scalable analytical foundations, connecting account health and product usage to actionable recommendations, and communicating findings through narratives, executive presentations, dashboards, and written recommendations. Salesforce describes Slack’s culture as positive, diverse, supportive, curious, inventive, hardworking, humble, and collaborative.

Requirements

At least 4 years of industry experience applying data science, statistics, or quantitative analysis to complex business problems.
Advanced SQL proficiency and proficiency in at least one data science programming language, such as Python, R, or Scala.
Strong foundation in statistics, experimentation, causal inference, predictive modeling, and analytical problem-solving.
Experience with large-scale data technologies such as Spark, Presto, Hive, Hadoop, or similar distributed data platforms.
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.
A related technical degree is required.

Nice To Haves

Knowledge of workflow orchestration tools such as Apache Airflow.
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.
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.

Responsibilities

Partner with GTM leadership to identify strategic opportunities, evaluate business performance, and influence business decisions.
Apply statistical methods, experimentation, and advanced analytics to understand customer behavior, sales performance, and growth drivers.
Develop predictive models, segmentation frameworks, and forecasting methodologies to improve GTM planning and execution.
Design measurement strategies and success metrics for 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 to uncover trends, quantify business impact, and support executive decision-making.
Partner with Data Engineering to develop trusted datasets and scalable analytical foundations for advanced modeling and experimentation.
Collaborate with Product and Sales Strategy to create intelligence solutions connecting account health, product usage, customer engagement, and seller actions to actionable recommendations.
Translate complex analyses into narratives, executive presentations, dashboards, and written recommendations for technical and non-technical audiences.
Promote evidence-based decision-making by improving access to trusted metrics, analytical methodologies, and strategic insights across the GTM organization.