Manager, Data Science Insights and Analytics

About the job

As a Manager, Data Science Insights and Analytics at Western Union, you will lead critical Machine Learning and Analytics projects and design scalable AI/ML applications with a focus on AWS environments. Your role involves managing a self-hosted data science platform, building ETL data pipelines, and acting as a bridge between business units, AI/ML teams, and external partners. You will provide technical solutions for AI, Data Science, and cloud architecture requirements, collaborate with Data Engineers, and create documentation for platform processes. Additionally, you will coordinate with IT for platform integrations, cloud infrastructure, and security alignment. • *Key Responsibilities:** - Lead ML and analytics projects from requirements gathering through technical design and delivery. - Design and deploy scalable AI/ML applications with a focus on AWS environments. - Manage a self-hosted data science platform, including user access controls, maintenance, and upgrades. - Build and maintain ETL data pipelines across AWS ecosystems. - Act as a bridge between business units, AI/ML teams, and external partners. - Perform advanced data analysis across multiple concurrent projects. - Provide technical solutions for AI, Data Science, and cloud architecture requirements. - Collaborate closely with Data Engineers on end-to-end project components. - Create documentation for platform processes and provide ongoing user support. - Coordinate with IT for platform integrations, cloud infrastructure, and security alignment. • *Role Requirements:** - Expertise in end-to-end ML solution development. - Proficiency in AWS architecture for model deployment, monitoring, and lifecycle management. - Understanding of MLOps, CI/CD workflows, cloud services, and data warehousing concepts. - Experience with ETL, data modeling, and BI tools. - Strong query-writing and data analysis skills. - Hands-on experience managing self-hosted platforms. - Familiarity with containerization, orchestration, and version control systems. - Knowledge of data governance, security best practices, and access control models. - Experience with Linux/Unix administration and relevant networking concepts. - Strong communication skills for guiding or mentoring team members. - BS in Computer Science or related field. - 8+ years of work experience with 4+ years in building, training, and deploying ML models. - Experience deploying models in AWS SageMaker or similar platforms. - Experience working with Snowflake. - Strong data analysis and SQL skills across platforms. - Hands-on experience with ETL tools such as Talend. - 2+ years of experience managing ML or Data platforms. - Ability to troubleshoot complex platform and infrastructure issues. - Experience with infrastructure-as-code and automation tools. • *Preferred Qualifications:** - Fintech industry domain knowledge. - Hands-on experience with ETL tools like Talend. - Experience managing cloud-based infrastructure (AWS, Azure, GCP). - Certifications in relevant cloud or data science technologies. - Knowledge of data science workflow optimization and best practices. - Experience in training and onboarding users on data science platforms. - Experience with Agentic AI workflows and LLM orchestration frameworks. - Hands-on experience building custom LLM applications and integrating them with enterprise systems. - Understanding of RAG, vector databases, and LLM deployment architectures.

Requirements

• Machine Learning
• Analytics
• AWS
• ETL
• Data Engineering

Qualifications

• BS in Computer Science or related field

Preferred Technologies

• Machine Learning
• Analytics
• AWS
• ETL
• Data Engineering

Benefits

• Health insurance options
• Accident and life insurance
• Development platforms

About the company

At Western Union, you will have access to short-term incentives, health insurance options, accident and life insurance, and development platforms. The company values in-person collaboration and supports a hybrid work model that allows flexibility between working from home and the office.