Sr. Manager, People Analytics
Levi Strauss
- Location
- IND, India-Bangalore GSC (827A)
- Work model
- On-Site
- Level
- Senior
- H-1B history
- 17 approvals (FY2023)
- Posted
- Aug 15, 2026
Skills
About this role
At Levi Strauss & Co., we believe great people power great brands. We're building our People Analytics function from the ground up. Today, it's focused on reporting and dashboards, and we're looking for someone who wants to lead its next chapter: making it a modern, AI-enabled function that gives HR and business leaders real answers, not just data. This role is for someone who has built people analytics capability before, not just operated within a function that was already mature. You'll set the strategy, manage a growing team, and be hands-on enough to build the first wave of solutions yourself, including bringing GenAI and automation into a function that isn't leveraging it yet. This role is based in India but serves as a global function lead. You'll partner with HR and business stakeholders across regions and time zones, so comfort working asynchronously and building trust with teams you don't see in person, is part of the job.
What You'll Do
Lead with Strategy Define and evolve a people analytics vision and roadmap appropriate to our current stage, moving deliberately from reporting-led to insight-led, and eventually to predictive. Translate business and HR priorities into a realistic, sequenced analytics roadmap. Build a fast, credible understanding of the business, its key drivers, and how workforce data connects to performance outcomes. Define and evolve workforce metrics and KPIs that matter across a global enterprise. Lead AI-Powered Innovation Bring people analytics into the AI era — identify and pilot GenAI tools for self-service insights, natural-language querying, and automated narrative reporting, so leaders can get answers without waiting on a dashboard request. As data foundations mature, introduce predictive analytics sequenced realistically, not promised on day one. Create and implement a plan to build AI and data literacy across HR, helping practitioners get comfortable using AI-assisted tools rather than depending entirely on the analytics team. Champion responsible and ethical use of AI in people decisions (bias awareness, transparency, and human oversight), distinct from, and in addition to, general data privacy compliance. Stay current on the evolving AI and data regulatory landscape across the regions we operate in, and flag emerging requirements to leadership early — partnering with Legal, Privacy, or other relevant functions as those partnerships formalize. Drive Technology and Continuous Improvement Shape and evolve the people analytics technology ecosystem, enabling scalable, efficient, and automated solutions. Partner with IT/Digital teams to align People Analytics needs with enterprise approach, especially on AI-enabled platforms and capabilities within Workday and adjacent tools. Continuously enhance reporting and analytics capabilities. Partner with HR, Finance, and IT to implement controls and processes that maintain data integrity across systems. Monitor and enhance analytics solutions to meet changing business needs. Build and Tell Data Stories (Hands-On) Evaluate existing dashboards for improvements and personally design and build dashboards, reports, and visualizations across multiple data sources, primarily using Power BI and Python/R. This is a hands-on role, especially in Year One. Define analytical approaches for complex employee and organizational questions. Turn complex data into clear, compelling narratives that drive leadership action. Create intuitive, scalable dashboards for audiences ranging from HRBPs to executive leadership. Own People Data Management at Scale Lead people data management in a global environment powered by Workday, recognizing that clean, governed data is the prerequisite for everything above it, including AI and predictive work. Establish data governance, standardized processes, and cross-system alignment where they don't yet exist. Oversee collection, transformation, and maintenance of large, complex datasets from multiple sources. Ensure data practices