Associate 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. We're looking for a sharp, curious, and driven Associate Data Scientist - someone who doesn't just crunch numbers but genuinely obsesses overturning data into impact. If you're passionate about Machine Learning, Generative AI, and Advanced Analytics and want to apply them to real, complex business problems - this is your launchpad. You'll work alongside seasoned Data Scientists, Data Engineers, and Software Engineers - collaborating directly with business stakeholders across verticals to build predictive models, generate actionable insights, and ship AI/ML solutions that operate on a scale. From forecasting and optimization to automation and GenAI applications - you'll get hands-on exposure to the full spectrum of modern Data Science. Primary Responsibilities: Analyze & Discover - explore structured and unstructured datasets through deep EDA, feature engineering, and data validation to uncover patterns that drive business decisions Build & Optimize - develop, evaluate, and fine-tune machine learning and statistical models that solve real problems Communicate & Influence - create dashboards, reports, and visualizations that translate complex findings into clear, actionable narratives for stakeholders Collaborate & Ship - work hand-in-hand with Data Engineers to build reliable data pipelines and deploy AI/ML solutions into production Automate & Improve - identify and drive process improvement and automation opportunities across business functions Document & Share - maintain clear documentation of methodologies, experiments, and technical solutions Learn & Evolve - stay on the cutting edge of AI, ML, Generative AI, and analytics - and bring those ideas back to the team 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. Must have Skills: Core Data Science - strong foundation in statistics, probability, ML/DL algorithms, and model evaluation techniques Python & SQL - solid proficiency; you think in Python and speak fluent SQL ML Toolkit - hands-on experience with Pandas, NumPy, Scikit-learn, and at least one deep learning framework (PyTorch / TensorFlow) Generative AI & LLMs - working knowledge of large language models (GPT, LLaMA, etc.), prompt engineering, and prompt optimization techniques RAG & Embeddings - understanding of Retrieval-Augmented Generation architectures, vector databases (FAISS, Pinecone, Weaviate), and embedding strategies LLM Frameworks - exposure to LangChain, LangGraph, or similar orchestration frameworks Communication - ability to distill complex analysis into clear insights for both technical and non-technical audiences Mindset - strong problem-solving instincts, intellectual curiosity, and a bias for action. Good to have skills : AI Agents & Autonomous Systems - experience building AI agents, chatbots, or agentic workflows that operate with minimal human intervention Multimodal AI - exposure to models spanning text, image, audio, or video (e.g., vision-language models, speech-to-text) Model Fine-Tuning - hands-on experience with LLM fine-tuning (LoRA, QLoRA, PEFT) and working with LLM APIs at scale MLOps / LLMOps - familiarity with model deployment pipelines, CI/CD for ML, experiment tracking (MLflow, Weights & Biases), and API serving Cloud & Containers - working knowledge of AWS (SageMaker, S3, Lambda) and Docker; bonus for Kubernetes exposure Real-World Problem Solving - experience with applied use cases like forecasting, optimization, automation, or recommendation systems Responsible AI - awareness of AI safety, bias mitigation, hallucination risks, and model governance practices Agile & Cross-Functional Collaboration - experience thriving in fast-paced, cross-functional team environments with iterative delivery cycles Documentation & Storytelling - ability to maintain clean technical documentation and present findings that drive decisions. Required Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field 1+ years of experience in Data Science, Machine Learning, Analytics, or related domains Experience with data analysis and machine learning libraries such as Pandas, NumPy, and Scikit-learn Understanding of supervised and unsupervised learning techniques Familiarity with data visualization tools such as Tableau, Matplotlib, or Seaborn Solid foundation in statistics, probability, and machine learning concepts Proficiency in Python and SQL Proven solid analytical, problem-solving, and communication skills Proven ability to work collaboratively in a cross-functional team environment Preferred Qualification: Basic understanding of cloud platforms, MLOps, or model deployment concepts 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.