Join Optum, a global leader in health optimization, and contribute to a healthier future for millions. Our mission is to connect people with the care, resources, and data they need to thrive. You'll be part of an inclusive culture, working alongside talented professionals and benefiting from comprehensive development opportunities. Make a tangible impact on communities worldwide as we advance health optimization on a global scale. Caring. Connecting. Growing together – this is our ethos.

Drive the creation and deployment of scalable AI/ML solutions using Python, SQL, and leading ML frameworks. Manage the complete ML lifecycle, from data preparation and feature engineering to model evaluation and continuous monitoring. Guide model selection, optimization, and tuning, balancing performance with explainability, cost, and Responsible AI principles. Build production-grade ML pipelines with tools like MLflow and vector databases. Lead drift analysis and model health monitoring for production systems. Design and support multi-cloud ML infrastructure (Azure/GCP, AWS) with a focus on distributed data processing. Collaborate with data engineering teams on real-time and batch pipelines, and translate business needs into technical solutions with engineering, product, and UX teams.

A Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related discipline is required, alongside over 12 years of experience in Data Science and AI/ML, including 2+ years in leadership roles. Candidates must possess hands-on experience with the full AI/ML project lifecycle, from EDA and model development to drift analysis, and have a proven track record of delivering production-grade AI/ML projects. Proficiency in Scikit Learn, TensorFlow, and PyTorch, coupled with strong Python, pandas, numpy, and SQL skills, is essential. A solid grasp of mathematical and statistical concepts, excellent problem-solving abilities, and strong communication and collaboration skills are also critical.