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About This Role
LOCATION: US – Denver
US – Atlanta
TYPE: Full time
WORK SHIFT: Hybrid
POSTED: June 5, 2026
ID: JR0130823
Overview
At Western Union, we’re more than a trusted name in global payments. We’re moving beyond remittances, beyond cash, and beyond the expectations of our customers.
Our talented teams enable us to transform into a digital\-first company, built on the strength of our retail foundation and powered by next\-generation payments. All this with the goal of helping people prosper.
Our customers inspire us to push boundaries and create services that make life easier and communities stronger. Wherever you are in the world, we’re committed to shaping the next generation of financial experiences.
Join us as we go beyond and be part of a team that’s redefining what’s possible.
Role Responsibilities
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.
People Data \& Analytics:
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
AI \& Automation Leadership:
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
Technical \& Data Engineering:
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
Consulting \& Stakeholder Influence:
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
Role Requirements
Required:
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
Preferred:
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
\*Applicants must be currently authorized to work in the United States on a full\-time basis. Western Union will not sponsor applicants for work visas for this position.
Work Shift
HYBRID – Western Union values in\-person collaboration, problem solving, and ideation whenever possible. We believe this fosters common ways of working and supports how we execute initiatives for our customers. The expectation is to work from the office a minimum of three days a week.
Location: 7001 E. Belleview Ave Denver, CO 80237 (preferred)
5 Concourse Pkwy NE, Suite 2300 Atlanta, GA 30328
BENEFITS AND OTHER DETAILS
Benefits
You will also have access to short\-term incentives, multiple health insurance options, accident and life insurance, and access to best\-in\-class development platforms, to name a few (https://careers.westernunion.com/global\-benefits/). Please see the benefits below specific to your country. If applicable, additional role\-specific benefits will be mentioned during your interview process or in an offer of employment.
Your United States specific benefits include:
Medical, Dental, Vision, and Life Insurance
Tuition Assistance Program
Employee Discount Program
Parental Leave
401K Plan
For residents of Colorado, California, Connecticut, Delaware, Minnesota, and Pennsylvania: Please do not respond to any questions on this initial application that may seek age\-identifying information such as age, date of birth, or dates of school attendance or graduation. You may also redact this information from any materials you submit during the application process. You will not be penalized for redacting or removing this information.
Salary
The base salary range is $110,000\-$140,000 per year; total on\-target earnings include a base salary and short\-term incentives that align with individual and company performance. Actual salaries will vary based on candidates’ qualifications, skills, and competencies.
Other Details
We are passionate about honoring our employee's identity and fostering a feeling of belonging. Our commitment is to provide an inclusive culture that celebrates the unique backgrounds and perspectives of our global teams while reflecting the communities we serve. We do not discriminate based on race, color, national origin, religion, political affiliation, sex (including pregnancy), sexual orientation, gender identity, age, disability, marital status, or veteran status. The company will provide accommodation to applicants, including those with disabilities, during the recruitment process, following applicable laws.
Estimated Job Posting End Date:
07\-06\-2026
This application window is a good\-faith estimate of the time that this posting will remain open. This posting will be promptly updated if the deadline is extended or the role is filled.
Salary Context
This $110K-$140K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1937 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Western Union, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($125K) sits 31% below the category median. Disclosed range: $110K to $140K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Western Union AI Hiring
Western Union has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Denver, CO, US. Compensation range: $140K - $140K.
Location Context
AI roles in Denver pay a median of $184,000 across 159 tracked positions. That's 8% below the national median.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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