Senior Staff Business Data Talent Analytics Lead (AI)

Location: San Diego, California, or Mountain View, California, United States

Base pay: $171,500–$231,500 in San Diego; $184,000–$249,000 in Mountain View, plus potential bonus, equity, and benefits.

Company

Global financial technology platform providing products including tax, credit, accounting, and marketing software.

What you will do

• Own the end-to-end data strategy for workforce planning, talent acquisition, and broader people analytics.
• Automate manual reconciliation and reporting processes to provide trusted, near real-time talent data.
• Influence how talent data is structured, stored, and moved across databases, warehouses, and pipelines.
• Build dashboards, visualizations, and self-service reporting for people leaders and business stakeholders.
• Build and deploy AI agents to deliver talent insights and automate recurring analytics tasks.
• Partner with senior stakeholders, executives, People, Talent Acquisition, Finance, and data engineering teams.

Requirements

• Bachelor’s degree in data analytics, business, human resources, industrial/organizational psychology, or a related field.
• 8+ years of business or data analytics experience, including talent analytics, workforce planning, recruiting analytics, or people analytics data.
• Strong hands-on experience building and deploying AI agents for talent insights at scale.
• Working knowledge of data warehouses, data pipelines, data architecture, and scalable analytics.
• Experience automating reporting, building dashboards or self-service tools, and enforcing data quality standards.
• Excellent communication skills with experience influencing senior stakeholders and executive leadership.

Nice to have

• Experience with Workday HCM data and Avature or other applicant tracking systems.
• Experience with talent acquisition funnel, sourcing, or recruiting pipeline metrics.
• Familiarity with people data governance, security, and access considerations.

Culture & Benefits

• High-visibility partnership with senior leadership and executive stakeholders.
• Competitive compensation with performance-based rewards.
• Potential cash bonus, equity rewards, and employee benefits.
• Work focused on scalable analytics, automation, and AI-enabled decision support.