Optum is a global leader dedicated to improving health outcomes through advanced technology and connected care. Our team is focused on making a tangible impact on people's lives by linking them to essential pharmacy benefits, data, and resources. We foster an inclusive environment with talented colleagues, comprehensive benefits, and ample career development opportunities. Join us in advancing global health optimization and contributing to the communities we serve. We are committed to Caring, Connecting, and Growing together.

Drive significant client value by developing cutting-edge predictive models using various machine learning algorithms and best practices.

Execute scripts for ML model inference, test hypotheses, and present findings to diverse audiences. Conduct cost-benefit analyses for data science initiatives.

Design, implement, and maintain robust CI/CD pipelines for MLOps and DevOps. Create essential artifacts like STM, HLD, and LLD to transition prototypes into production.

Leverage expertise in data modeling, statistics, machine learning, programming, and advanced mathematics to uncover patterns, identify opportunities, and formulate business questions that drive valuable discoveries and actionable insights. Analyze and interpret data using tools like SQL, R, Python, and Hadoop.

Communicate machine learning algorithm performance effectively across interdisciplinary teams.

Create impact at scale by developing and managing a comprehensive catalog of scalable data services to enhance analytical offerings. Proactively seek opportunities for continuous improvement and optimization of production models. Champion ML architecture and workflow best practices, and collaborate with business intelligence architects to maximize the effectiveness of BI tools and reporting capabilities.

Address complex, unstructured issues and serve as a knowledgeable resource for colleagues. Ensure adherence to all applicable Company policies and directives, including those concerning work location, team assignments, schedules, and flexible work arrangements.

A Bachelor's Degree in a relevant field such as Information Technology, Engineering, Mathematics, Computer Science, or Analytics is required.

Possess at least 5 years of hands-on experience in data science projects and active development.

Demonstrate 5+ years of experience with Microsoft Azure Cloud, Databricks, MLflow, Spark SQL, and Python.

Proficiency in applying a wide range of Machine Learning Algorithms, including Linear & Logistic Regression, Time Series Analysis, Support Vector Machines, K-Means Clustering, K-Nearest Neighbors, Decision Trees, Random Forests, Naive Bayes, PCA, SVD, Artificial Neural Networks, Association Rules, Genetic Algorithms, Optimization, Bagging, and Boosting algorithms.

Solid understanding of data, schema, data models, machine learning principles, and optimizing big data lifecycles.

Strong hands-on experience in Python coding, Spark SQL, and other relevant programming languages and their packages.

Proven ability to generate opportunities through machine learning or artificial intelligence.

Exceptional communication and presentation skills, coupled with strong analytical and problem-solving abilities.

Demonstrated cooperative and team-player attitude.

Ability to design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, effectively translating business needs into scalable applications that enhance products, workflows, and decision-making.