Senior Lead - Workforce Intelligence

Salesforce Salesforce · Enterprise · Tokyo, Japan

Salesforce is seeking a Lead, Workforce Intelligence to 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. The role involves designing analytical frameworks, developing machine learning and LLM solutions, creating reusable intelligence assets, and partnering closely with engineering teams to operationalize workforce intelligence capabilities. Responsibilities include analyzing employee feedback, collaboration patterns, communication signals, and workforce datasets using NLP, network analysis, ML, and LLMs, and partnering with data engineering to operationalize new sensing capabilities.

What you'd actually do

  1. Design and execute innovative workforce intelligence studies that combine employee listening, behavioral science, and advanced analytics to better understand employee experiences and organizational outcomes.
  2. Identify, evaluate, and operationalize emerging workforce data sources and employee listening data.
  3. 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.
  4. Build analytical frameworks and data products that enable workforce insights to be generated consistently, efficiently, and at scale.
  5. Partner closely with Data Engineering, HR Technology, and platform teams to define technical requirements, data models, and architectures that support workforce intelligence initiatives.

Skills

Required

  • Data Science
  • Data Engineering
  • Behavioral Science
  • People Analytics
  • Machine Learning
  • Large Language Models (LLMs)
  • Natural Language Processing (NLP)
  • Network Analysis
  • Topic Modeling
  • Embeddings
  • Clustering
  • Classification
  • Data Products
  • Technical Requirements Definition
  • Data Models
  • Architectures
  • Organizational Network Analysis
  • Collaboration Intelligence
  • Employee Feedback Analysis
  • Data Governance
  • Responsible AI
  • Research Methodology

Nice to have

  • Computational Social Science
  • Employee Research
  • Applied AI
  • Consulting Mindset
  • Intellectual Curiosity
  • Stakeholder Influence
  • Complex Analytical Concept Communication

What the JD emphasized

  • operationalize
  • scalable
  • workforce intelligence
  • employee listening
  • large language models

Other signals

  • develop machine learning and LLM solutions
  • operationalize workforce intelligence capabilities
  • transform fragmented workforce data into scalable intelligence
  • apply methods such as natural language processing, network analysis, machine learning, and large language models
  • operationalize new workforce sensing capabilities
  • advancing how Salesforce leverages employee listening, collaboration signals, and digital trace data