Lead - Workforce Intelligence

Job Overview

Salesforce is seeking a Lead, Workforce Intelligence to help shape the future of employee listening and organizational research. This role sits at the intersection of data science, data engineering, behavioral science, and people analytics, helping transform complex workforce and employee experience data into scalable intelligence that drives strategic business decisions.

As a member of the Workforce Intelligence team, you will partner with researchers, analysts, HR leaders, and technical teams to transform workforce data into actionable insights that inform strategic decisions across the company. You will help establish scalable approaches for analyzing employee feedback, collaboration patterns, communication signals, and emerging workforce datasets while ensuring insights remain interpretable, actionable, and grounded in sound scientific principles.

• Design and execute innovative workforce intelligence studies that combine employee listening, behavioral science, and advanced analytics to better understand employee experiences and organizational outcomes.
• Identify, evaluate, and operationalize emerging workforce data sources and employee listening data.
• Develop scalable approaches for transforming unstructured workforce data into reusable intelligence assets through methods such as topic modeling, embeddings, large language models, clustering, and classification.
• Build analytical frameworks and data products that enable workforce insights to be generated consistently, efficiently, and at scale.
• Partner closely with Data Engineering, HR Technology, and platform teams to define technical requirements, data models, and architectures that support workforce intelligence initiatives.
• Prototype and operationalize new analytical capabilities, helping bridge the gap between exploratory research and production-ready workforce intelligence solutions.
• Lead the development of organizational network analysis and collaboration intelligence capabilities to better understand patterns of influence, connectivity, and information flow across the enterprise.
• Design scalable approaches for coding, categorizing, summarizing, and synthesizing large volumes of employee feedback and unstructured workforce data.
• Translate complex analytical findings into compelling narratives, visualizations, and recommendations for senior leaders and stakeholders.
• Serve as a thought partner to Employee Listening, HR Business Partners, Talent teams, and executive stakeholders on emerging workforce trends and opportunities.
• Stay current on advances in AI, computational social science, workforce sensing, employee listening, and organizational research methodologies, identifying opportunities to apply new approaches within Salesforce.
• Champion best practices in workforce intelligence, responsible AI, data governance, and research methodology.

• Master's degree or PhD in Data Science, Statistics, Computer Science, Economics, I/O Psychology, Organizational Behavior, Computational Social Science, or a related quantitative discipline.
• 5+ years of experience in workforce intelligence, people analytics, employee listening, data science, applied research, survey science, computational social science, or a related field.
• Advanced proficiency in SQL as well as either Python or R, with demonstrated experience building production-quality analytical workflows and scalable data solutions.
• Experience applying natural language processing, large language models, text analytics, topic modeling, embeddings, clustering, network analysis, or related advanced analytical methods.
• Experience designing scalable analytical workflows, reusable data assets, or data products that support broader organizational decision-making.
• Familiarity with collaboration, communication, employee listening, workforce, behavioral, or organizational datasets is strongly preferred.
• Experience working closely with Data Engineering, platform, or technology teams to operationalize analytical solutions and data assets.
• Knowledge of cloud-based analytics environments (e.g., AWS) and modern data ecosystems.
• Experience building or supporting data…