Senior 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.

This role focuses on developing advanced analytical and machine learning solutions to support enterprise AI initiatives, particularly Defensive AI, risk intelligence, and AIdriven automation programs. The role emphasizes translating complex data into actionable insights and AIready models.

Primary Responsibilities:

• Data Science & Advanced Analytics
  • Develop and deploy statistical models and machine learning algorithms using Python
  • Perform exploratory data analysis (EDA) to identify trends, risks, and actionable insights
  • Design and evaluate models for classification, regression, clustering, and anomaly detection
• AI / ML Model Development
  • Build and optimize ML models supporting Defensive AI, automation, and intelligence use cases
  • Perform feature engineering and model tuning for performance, scalability, and explainability
  • Prepare and validate datasets for GenAI, LLM, and advanced ML workflows
• Model Deployment & Lifecycle
  • Partner with data engineering and platform teams to operationalize models
  • Support model monitoring, performance tracking, and continuous improvement
  • Ensure models align with enterprise standards for security, governance, and compliance
• CrossFunctional Collaboration
  • Collaborate closely with Data Engineering, AI Platform, Product, and Security teams
  • Translate business problems into data science solutions and measurable outcomes
  • Communicate insights and model results clearly to technical and nontechnical stakeholders
• 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 regards 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:

• Experience working with large, complex, enterprisescale datasets
• GenAI / LLM data preparation and understanding of promptready datasets
• Proven solid Python for data analysis, ML modeling, and automation
• Proven applied statistics & machine learning (classification, regression, anomaly detection)
• Proven feature engineering & model evaluation techniques
• Proven SQL for data analysis and largescale dataset exploration

Preferred Qualifications:

• Experience working in Agile, crossfunctional product teams
• Knowledge of cloud platforms (Azure preferred)
• Familiarity with MLOps, model monitoring, and CI/CD for ML
• Proven exposure to Databricks / Spark / Big Data ecosystems