Lead Data Scientist

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Optum is a global organization dedicated to transforming healthcare through technology, data, and intelligence. The work you do here will directly impact the lives of millions by improving access to care, optimizing pharmacy benefits, and enabling data-driven decisions across the healthcare ecosystem.

Lead development and deployment of an AI-driven Payment Integrity platform to detect claim anomalies and prevent inappropriate payments. Design and implement machine learning models, big data pipelines, and automation solutions to replace manual processes. Collaborate with cross-functional teams to ensure compliance, reduce financial leakage, and mitigate risks such as up-coding, modifier misuse, and policy violations.

Primary Responsibility:

• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Undergraduate degree or equivalent experience
• Advanced degree in Data Science, Computer Science, or related field. Proven experience in AI/ML model development, big data technologies, and cloud platforms (Azure preferred)
• 
  Solid skills in Python, SQL, Spark, and Agile/Scrum methodologies. Expertise in healthcare claims, payment integrity, and compliance frameworks is highly desirable. Solid expertise in Python (basic and advanced concepts) for ML and data engineering workflows
• Extensive experience with Big Data technologies including PySpark, Spark, and Databricks
• Practical experience with Jupyter and cloud platforms such as Azure, AWS, or GCP
• Hands?on experience in LLM text generation using APIs and agent frameworks
• Experience building classification models using BERT or other Transformer architectures
• Practical MLOps experience including model deployment, monitoring, and lifecycle management
• Hands?on experience with LLMs, Transformer-based models, embeddings, and advanced NLP applications
• Hands?on proficiency with Git, MLflow, cloud ML services, Kubernetes, and Terraform
• Deep understanding of BERT, Transformers, and embeddings for NLP and GenAI solutions
• Ability to design and implement RAG (Retrieval Augmented Generation) models
• Solid knowledge of guardrailing techniques for safe and compliant LLM deployments
• Expertise in developing, deploying, and optimizing end?to?end ML and GenAI solutions
• Solid command over Python-based data workflows and distributed Big Data systems

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• Proven ability to design scalable ML architectures, orchestrate pipelines, and ensure production reliability
• Deep understanding of MLOps practices for model lifecycle management and enterprise-level deployment
• Solid leadership skills with the ability to mentor teams, drive technical decisions, and influence stakeholders

Preferred Qualifications:

• Experience with tree?based models, regression/classification techniques, time series, clustering, and model optimization
• Experience building and orchestrating pipelines using Databricks workflows
• Team management experience including roadmap planning, prioritization, architecture design, and stakeholder management
• Solid foundation in advanced statistics and scalable architecture for ML systems
• Expertise in data cleaning, EDA, feature engineering, and scalable ETL/ML pipelines
• Solid leadership qualities with effective decision?making, mentoring, and strategic communication