Requisition Number: 2362793 Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. Transform Healthcare Through AI Innovation at Optum Optum is a global organization delivering care, powered by data and technology, to help millions of people live healthier lives. At Optum.ai, we are not just witnessing the AI transformation in healthcare-we are leading it. Our mission is clear: to simplify healthcare with AI, turning insight into action at a scale few organizations in the world can match. As part of the Optum.ai team, you'll work at the intersection of cutting-edge artificial intelligence and real-world healthcare impact. From reducing administrative burden for providers to anticipating patient needs and improving access to quality care, your work will help solve some of healthcare's most complex challenges-and directly improve health outcomes for millions of people. You'll collaborate with world-class talent across data science, engineering, product, and healthcare domains, backed by the reach and stability of Optum and UnitedHealth Group. Here, responsible innovation matters. So do comprehensive benefits, meaningful career growth, and the opportunity to make a tangible difference-advancing health equity and creating a simpler, more connected healthcare experience for everyone. This is more than a job. It's a chance to shape the future of healthcare through the transformative power of AI. Optum AI is UnitedHealth Group's enterprise AI team. We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for healthcare. We develop AI/ML solutions for the highest impact opportunities across UnitedHealth Group businesses including UnitedHealthcare, Optum Financial, Optum Health, Optum Insight, and Optum Rx. In addition to transforming the healthcare journey through responsible AI/ML innovation, our charter also includes developing and supporting an enterprise AI/ML development platform. As a Principal Data Scientist, you will serve as a senior individual contributor responsible for designing and delivering advanced AI/ML and Generative AI systems that address complex healthcare and operational challenges. You will lead the development of large-scale machine learning solutions, architect GenAI and agent-based systems, and drive technical innovation across high-impact AI initiatives. This role requires deep hands-on expertise in machine learning, LLM systems, distributed AI architectures, and production-grade ML platforms. You'll enjoy the flexibility to work remotely* from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. Primary Responsibilities: - Lead development of advanced AI/ML systems using techniques such as deep learning, representation learning, time-series modeling, survival analysis, and probabilistic modeling to solve complex healthcare problems - Develop Generative AI and LLM-powered solutions including retrieval-augmented generation (RAG) pipelines, domain-adapted LLMs, and AI copilots for enterprise workflows - Architect scalable AI and ML systems including feature engineering pipelines, feature stores, model training workflows, model serving infrastructure, monitoring systems, and automated retraining pipelines - Build agentic AI and autonomous workflows using agent frameworks, agentic skills, MCP integrations, and agent-to-agent (A2A) communication patterns - Advance model evaluation, reliability, and monitoring strategies including offline metrics, LLM benchmarking, safety testing, hallucination mitigation, and drift detection - Drive responsible AI practices including explainability, interpretability, bias detection, fairness evaluation, and governance aligned with enterprise and regulatory standards - Serve as a senior technical authority in AI/ML by mentoring data scientists and reviewing complex modeling approaches and architectures - Collaborate with engineering, platform, and product teams to operationalize scalable AI/ML and GenAI systems within enterprise platforms You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications: - 10+ years of experience in machine learning, artificial intelligence, or applied data science with 7+ years of designing and deploying production machine learning systems - 8+ years of experience in Python-based machine learning development using frameworks such as PyTorch, TensorFlow, or equivalent along with solid SQL skills - 5+ years of experience deploying production ML systems including model serving, monitoring, ML lifecycle management, and collaboration with engineering teams - 3+ years of experience developing Generative AI or LLM-based applications including prompt engineering, RAG pipelines, LLM evaluation, and safety guardrails - 1+ years of experience building or evaluating agentic AI systems including AI agents, agentic skills, Model Context Protocol (MCP), agent-to-agent (A2A) interaction patterns, or autonomous workflows Preferred Qualifications: - Experience working with distributed ML systems and large-scale data platforms such as Spark, Databricks, Ray, or Kubernetes-based ML systems - Experience deploying AI solutions on cloud platforms such as AWS, Azure, or GCP - Experience working with healthcare datasets and standards such as claims, EHR, ICD, CPT, SNOMED, FHIR, or HL7 - External contributions such as publications, patents, or open-source projects in machine learning or generative AI *All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy. Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable. Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment. #OptumTechPJ

• Atuar no ciclo de vida completo (end-to-end) de projetos de Data Science e Machine Learning: entendimento de negócio, preparação de dados, modelagem, avaliação e deployment. • Desenvolver e arquitetar soluções avançadas de IA Generativa, aplicando técnicas de LLMs, RAG, Prompt Engineering e integrações com provedores como OpenAI e AWS Bedrock. • Realizar análise exploratória (EDA), tratamento e transformação de volumes expressivos de dados estruturados e não estruturados. • Construir, validar e otimizar pipelines de ML e Deep Learning focando em escalabilidade, performance e confiabilidade. • Aplicar boas práticas de Engenharia de Software e MLOps para garantir a qualidade, testabilidade e continuous deployment dos modelos. • Colaborar diretamente com stakeholders técnicos e de negócios para traduzir desafios complexos em soluções analíticas de alto impacto.

• Conducting statistical analyses and data visualizations to identify trends and patterns in clinical trial data • Collaborating with cross-functional teams to ensure data integrity and adherence to study protocols • Assisting in the development of analytical models and tools to improve data analysis processes • Preparing reports and presentations that effectively communicate findings to stakeholders • Staying updated on industry trends and advancements in data science to contribute to innovative practices

Role Description We are seeking a highly analytical and curious Data Scientist to transform complex, real-world data into meaningful insights and scalable machine learning solutions. In this role, you will work across the full data lifecycle—partnering with data engineering and business teams to explore, clean, and understand diverse datasets, and translating those insights into models, experiments, and data-driven recommendations. You will play a critical role in bridging raw data and business impact, developing a deep understanding of how data is generated, structured, and used. This includes conducting rigorous exploratory analysis, assessing data quality and lineage, and building robust analytical datasets that power advanced modeling and reporting. This role offers the opportunity to work with large-scale data platforms, cloud infrastructure, and modern machine learning frameworks, while contributing to impactful decision-making through experimentation, analytics, and self-service data tools. Responsibilities - Collect, clean, and analyze large structured and unstructured datasets from multiple internal and external sources - Conduct thorough exploratory data analysis (EDA) to understand data distributions, relationships, outliers, and missing value patterns - Profile and audit datasets to assess data quality, completeness, consistency, and fitness for modeling - Investigate and document data lineage — understanding where data originates, how it flows, and how it transforms across systems - Identify and resolve data anomalies, inconsistencies, and integrity issues in collaboration with data engineering teams - Develop a deep understanding of the business domain and the underlying data that represents it — including what each field means, how it is captured, and what its limitations are - Translate raw, messy, real-world data into clean, well-understood analytical datasets ready for modeling and reporting - Apply statistical techniques such as correlation analysis, hypothesis testing, variance analysis, and distribution fitting to extract meaningful signals from noise - Build and deploy machine learning models including regression, classification, clustering, NLP, and time-series analysis - Design, evaluate, and analyze A/B experiments and controlled tests using causal inference techniques - Develop data-driven recommendations backed by rigorous statistical reasoning - Write clean, production-ready code in Python or R - Collaborate with data engineers to build reliable data pipelines and feature stores - Deploy and monitor ML models using MLOps best practices on cloud infrastructure - Build dashboards and self-serve analytics tools to support stakeholder decision-making Data Understanding & Analysis Skills - Strong ability to interrogate unfamiliar datasets and quickly develop a working understanding of their structure, semantics, and quirks - Experience working with messy, incomplete, or poorly documented real-world data - Skilled in identifying hidden patterns, trends, seasonality, and anomalies through visual and statistical exploration - Ability to ask the right questions about data — challenging assumptions, validating sources, and understanding the context in which data was collected - Proficiency in data profiling, descriptive statistics, and summary reporting to communicate the shape and health of a dataset - Experience creating data dictionaries, documentation, and data quality reports to support team-wide data understanding - Comfort working across structured (relational tables), semi-structured (JSON, XML), and unstructured (text, logs, sensor streams) data formats Technical Skills Required - Proficiency in Python (pandas, NumPy, scikit-learn, PyTorch or TensorFlow) and/or R - Strong SQL skills with hands-on experience in DB2 and SQL Server - Experience with Databricks for large-scale data processing, feature engineering, and model training - Familiarity with cloud platforms: Azure or AWS - Experience with data warehouses and big data platforms (Databricks, Snowflake, or Redshift) - Knowledge of MLOps tools such as MLflow, Kubeflow, or Airflow - Experience with streaming data technologies such as Kafka or Spark - Solid foundation in probability, statistics, linear algebra, and experimental design Nice to Have - Experience with deep learning, NLP, computer vision, or Bayesian methods - Familiarity with real-time or streaming data pipelines - Open-source contributions or published research