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.
Skills Required
- 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
- Proficiency in Python
- Proficiency in SQL
- Experience with Pandas, NumPy, and Scikit-learn
- Hands-on experience with at least one deep learning framework (PyTorch or TensorFlow)
- Working knowledge of large language models (e.g., GPT, LLaMA), prompt engineering, and optimization techniques
- Understanding of Retrieval-Augmented Generation (RAG), embeddings, and vector databases (FAISS, Pinecone, Weaviate)
- Exposure to LLM orchestration frameworks (LangChain, LangGraph, or similar)
- Familiarity with data visualization tools such as Tableau, Matplotlib, or Seaborn
- Solid foundation in statistics, probability, and machine learning concepts
- Proven analytical, problem-solving, communication skills and ability to work collaboratively in cross-functional teams
- Basic understanding of cloud platforms, MLOps, or model deployment concepts
- Experience with model fine-tuning (LoRA, QLoRA, PEFT) and LLM APIs at scale
- Familiarity with MLOps/LLMOps tools, experiment tracking (MLflow, Weights & Biases), CI/CD for ML, and API serving
- Working knowledge of AWS services (SageMaker, S3, Lambda), Docker, and optionally Kubernetes
- Experience with AI agents, multimodal AI, or applied use cases (forecasting, optimization, recommendations)
- Awareness of Responsible AI practices (bias mitigation, hallucination risks, model governance)
Optum Compensation & Benefits Highlights
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Healthcare Strength — Health coverage offers copay and HSA medical options with dental, vision, company‑paid life and disability, and free or low‑cost virtual visits. Feedback suggests the offering is comprehensive and competitive on paper.
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Parental & Family Support — Time off and family supports include PTO, eight paid holidays plus a floating day, six weeks paid parental leave, up to two weeks paid caregiver leave, Bright Horizons back‑up care, and adoption assistance up to $10,000. Feedback suggests these resources are meaningful for caregivers and family needs.
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Retirement Support — Savings programs include a 401(k) with employer match (after one year, vesting after two) and a 10%‑discount Employee Stock Purchase Plan. These programs bolster long‑term financial security when combined with other savings resources.
Optum Insights
What We Do
Optum, part of the UnitedHealth Group family of businesses, 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. At Optum, we support your well-being with an understanding team, extensive benefits and rewarding opportunities. By joining us, you’ll have the resources to drive system transformation while we help you take care of your future. We recognize the power of connection to drive change, improve efficiency and make a difference in health care. Join a team where your skills and ideas can make an impact and where collaboration is key to creating technology that produces healthier outcomes.
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Optum Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Optum has three workplace models that balance the needs of the business and the responsibilities of each role. These models, core on‑site (5 days/week), hybrid (4 days/week) and telecommute or fully remote, vary by country, role and location.