Data Scientist

This role within UnitedHealth Group supports advanced AI development for War Room analytics, helping build and operationalize analytics and AI capabilities for critical operational events. The work includes developing machine learning and generative AI workflows that improve issue detection, root-cause understanding, and executive-level visibility.

Responsibilities

• Design, develop, and implement advanced analytics and AI capabilities for War Room analytics and operational event management
• Analyze operational signals, incident trends, business impacts, and technology indicators to improve faster issue detection and escalation awareness
• Use machine learning, natural language processing, and AI techniques for anomaly detection, signal classification, summarization, and insight generation
• Partner with operations, business, analytics, data engineering, and technology stakeholders to translate War Room needs into scalable analytical solutions
• Document analytical approaches, assumptions, AI outputs, and operational insights in formats that are clear and consumable for business and technology audiences
• Develop, test, and validate analytical models and AI-enabled outputs for issue detection, root-cause analysis, operational prioritization, and executive visibility
• Prepare, clean, explore, and transform structured and unstructured data from operational, technology, business, and event-management sources
• Apply statistical analysis, machine learning, and data visualization to convert operational signals into actionable intelligence
• Build reusable code, analytical workflows, model evaluation routines, and automation assets using Python and related analytics libraries
• Monitor model and workflow outputs to support continuous improvement, response accuracy, and operational usefulness
• Support generative AI development for operational event summarization, root cause insight generation, executive brief creation, and War Room intelligence workflows
• Contribute to AI-enabled workflows that reduce manual analysis effort and increase speed and consistency of operational event response
• Apply prompt engineering, retrieval-based approaches, and model evaluation techniques to produce reliable and explainable AI outputs
• Follow responsible AI, data privacy, model governance, and documentation standards while building analytics and AI solutions
• Contribute to scalable data science solutions, analytical pipelines, and AI-enabled capabilities
• Work with data engineering teams to access, validate, and integrate data required for analytics and model development
• Support testing, troubleshooting, optimization, and production readiness of analytics and AI solutions
• Participate in Agile delivery routines including sprint planning, demos, and solution reviews
• Maintain strong coding standards, version control practices, and documentation across assigned work
• Collaborate with business, operations, analytics, product, and technology stakeholders to understand requirements and deliver analytical outputs
• Translate business questions into data analysis, model development, dashboards, and insights
• Communicate findings, model results, and recommendations clearly to technical and non-technical audiences
• Support senior team members in business reviews, solution walkthroughs, and analytical recommendations
• Participate in experimentation and proof-of-concept development for emerging analytics, advanced AI, and War Room intelligence capabilities
• Identify opportunities to improve operational event analytics, incident intelligence workflows, and executive reporting outputs
• Develop reusable analytical assets, code templates, insight frameworks, and documentation to improve delivery efficiency
• Continuously learn new data science and AI techniques relevant to operational intelligence, event response, and executive visibility

Requirements

• 3+ years of experience in Data Science, Analytics, Machine Learning, Artificial Intelligence, or related disciplines
• Hands-on experience with Python and analytics libraries including Pandas, NumPy, Scikit-Learn, TensorFlow, or PyTorch
• Experience working with structured and unstructured data, including data preparation, feature engineering, and exploratory analysis
• Working knowledge of machine learning, statistical modeling, natural language processing, and model evaluation techniques
• Ability to communicate analytical results, insights, and recommendations clearly to business and technical stakeholders
• Strong problem-solving skills, attention to detail, and the ability to work effectively in a collaborative team environment

Technologies

• Python, Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch
• Databricks, Azure AI, Snowflake
• LLMs, Generative AI, RAG, prompt engineering, AI agents

Preferred Qualifications

• Experience in Customer Experience, Contact Center Quality, Customer Interaction Analytics, or Operational Excellence environments
• Experience with Databricks, Azure AI, Snowflake, or modern cloud analytics platforms
• Experience working in Agile delivery environments with cross-functional product, analytics, and technology teams
• Exposure to Voice Analytics, Speech Analytics, Quality Monitoring, Sentiment Analysis, and Conversational AI use cases
• Familiarity with LLMs, Generative AI, RAG concepts, prompt engineering, AI agents, and responsible AI practices

Location and Work Setting

San Juan, PR (onsite)