Manager, People Analytics & AI

Western Union•Atlanta, GA

1d•$110,000 - $140,000•Hybrid

About The Position

As a Manager, People Analytics & AI, you will operate as a highly strategic Individual Contributor (IC) responsible for advancing the organization's People Analytics capabilities through data-driven insights, intelligent automation, and AI-enabled solutions. This role sits at the intersection of HR, data science, and emerging AI technologies, and is ideal for someone who can both perform deep analytical work and build scalable solutions that transform how HR operates. You will play a critical role in evolving the function beyond traditional reporting, driving the development of predictive insights, AI-driven decision support, and automated processes that enhance how HR operates.

Requirements

Bachelor’s degree in Data Analytics, Computer Science, Information Systems, Statistics, Mathematics, Business Analytics, or a related field with 5+ years of experience, or equivalent combination of education and experience
Strong proficiency in SQL and experience working with large, complex datasets
Experience building or working with AI/ML models, Large Language Models (LLMs), or AI-driven tools
Hands-on experience developing AI agents, copilots, or automation workflows
Proven ability to translate business needs into data solutions and actionable insights
Strong analytical and problem-solving skills with the ability to work effectively in complex and evolving environments
Experience collaborating across cross-functional teams and influencing stakeholders through data-driven recommendations
Ability to independently drive projects from problem definition through execution
Strong communication skills with the ability to present complex concepts clearly to both technical and business audiences
Hands-on experience using AI tools and technologies to improve productivity and accelerate solution development
Ability to evaluate AI-generated outputs and apply sound judgment regarding accuracy, quality, and business relevance
Advocates for innovation, automation, and responsible AI adoption while maintaining high standards of quality and governance

Nice To Haves

Preferred experience with Python or similar programming languages for data analysis or automation
Preferred understanding of data engineering concepts including ETL pipelines, data modeling, APIs, and system integrations
Preferred experience building dashboards and data visualizations using Power BI, Tableau, or similar tools
Preferred experience working with HR data and systems such as Workday or related platforms – though not required!
Preferred experience with cloud-based data platforms including Snowflake and related analytics technologies

Responsibilities

Design and deliver end-to-end analytics solutions across key HR domains including hiring, performance management, and engagement
Translate ambiguous business questions into structured data problems and actionable insights
Build and maintain scalable datasets, dashboards, and metrics frameworks to support leadership decision-making
Partner with HR, Finance, and business leaders to drive data-informed workforce strategies
Lead the development of AI-enabled solutions such as copilots, chatbots, and agent-based workflows to scale HR support and impact, including employee self-service, HR case triage, and talent insights
Partner with Technology and data teams to ensure AI solutions are secure, scalable, and integrated with existing systems
Explore and evaluate emerging AI technologies and tools to improve operational efficiency and enhance employee and HR experiences
Write and optimize SQL queries to extract, transform, and analyze data from systems such as Snowflake, Workday, and related platforms
Build and maintain data pipelines and data models to ensure reliable, high-quality datasets
Integrate data across Workday, recruiting, engagement, and related platforms to create a trusted source of workforce data
Act as a strategic advisor to HR and business leaders by providing insights and recommendations backed by data
Communicate findings and recommendations effectively to both technical and non-technical audiences, including executive leadership
Proactively identify opportunities to improve processes, reduce manual work, and increase self-service capabilities