Data Scientist
Optum
•
Minnetonka, MN
0
0
0
0
Not Applicable
Posted March 26, 2026
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Responsibilities
Commitments
Responsibilities
- Design, train, finetune, and deploy Large Language Models (LLMs) and Generative AI components for claims automation, anomaly detection, and investigative workflows
- Build and operationalize ML pipelines using Python, PySpark, and cloud-native architectures (Azure/AWS/GCP)
- Develop traditional machine learning models (classification, anomaly detection, NLP pipelines) for high‑volume healthcare datasets
- Implement RAG (Retrieval‑Augmented Generation) systems, embedding models, and vector database integrations
- Develop automated data processing, feature engineering, and model training pipelines using Spark, MLflow, Databricks, and big‑data ecosystems
- Partner with product, engineering, and clinical domain teams to translate complex business challenges into scalable ML and GenAI solutions
- Optimize and monitor ML models in production, ensuring accuracy, latency, compliance, and responsible‑AI best practices
- Present AI/ML solution designs, model insights, and GenAI architecture recommendations to technical and non‑technical stakeholders
- Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI
- 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.
Commitments
You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges.
All Telecommuters will be required to adhere to UnitedHealth Group's Telecommuter Policy.
We comply with all minimum wage laws as applicable.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected.
UnitedHealth Group is a drug - free workplace.
Candidates are required to pass a drug test before beginning employment.
Not Met Priorities
What still needs stronger evidence
Requirements
- 5+ years of hands‑on experience in AI/ML engineering, deep learning, or applied machine learning
- 3+ years of experience in Python, PySpark, ML frameworks (TensorFlow, PyTorch), and distributed training
- 3+ years of experience with big‑data systems (like Hadoop, Spark, Hive) and cloud platforms (like Azure, AWS, GCP)
- 2+ years of experience with LLMs, including:
- Finetuning (LoRA, QLoRA, PEFT, SFT, or RLHF)
- Prompt engineering & system design
- Prior experience with US healthcare datasets (claims, clinical, EMR/EHR, provider networks, payer ops)
- Experience deploying ML/LLM workloads using Databricks, MLflow, Kubernetes, or serverless inference
- Familiarity with modern GenAI tooling (LangChain, LlamaIndex, HuggingFace, OpenAI/Anthropic/Azure‑OpenAI APIs)
- Knowledge of deep learning architectures (Transformers, sequence models, contrastive learning)
- Experience optimizing model inference using quantization, distillation, or distributed GPU compute
- Demonstrated success in AI product delivery, cross‑functional collaboration, and influencing technical strategy
Preferred Skills
- Finetuning (LoRA, QLoRA, PEFT, SFT, or RLHF)
- RAG pipelines & vector search Preferred Qualifications
- Prior experience with US healthcare datasets (claims, clinical, EMR/EHR, provider networks, payer ops)
- Experience deploying ML/LLM workloads using Databricks, MLflow, Kubernetes, or serverless inference
- Familiarity with modern GenAI tooling (LangChain, LlamaIndex, HuggingFace, OpenAI/Anthropic/Azure‑OpenAI APIs)
- Knowledge of deep learning architectures (Transformers, sequence models, contrastive learning)
- Experience optimizing model inference using quantization, distillation, or distributed GPU compute
- Demonstrated success in AI product delivery, cross‑functional collaboration, and influencing technical strategy
- Strong grounding in ML fundamentals (feature engineering, model evaluation, A/B testing, MLOps best practices)
Education
- (Not required) – Bachelor's degree in CS or IT related field
- (Not required) – 5+ years of hands‑on experience in AI/ML engineering, deep learning, or applied machine learning
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 are the UHC Payment Integrity AI/ML Engineering Team, responsible for designing and deploying advanced Machine Learning and Generative AI solutions that prevent Fraud, Waste, and Abuse (FWA) across the healthcare claims ecosystem.
Our work spans pre‑payment prediction, post‑payment anomaly detection, intelligent automation, and next‑generation LLM‑based decisioning.
The team is a blend of AI/ML engineers, data scientists, data engineers, and GenAI specialists who collaborate to build and scale end‑to‑end ML systems. We align closely with the organization's mission of improving affordability, operational efficiency, and trust in healthcare data
You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges.
Primary Responsibilities
Design, train, finetune, and deploy Large Language Models (LLMs) and Generative AI components for claims automation, anomaly detection, and investigative workflows
Build and operationalize ML pipelines using Python, PySpark, and cloud-native architectures (Azure/AWS/GCP)
Develop traditional machine learning models (classification, anomaly detection, NLP pipelines) for high‑volume healthcare datasets
Implement RAG (Retrieval‑Augmented Generation) systems, embedding models, and vector database integrations
Develop automated data processing, feature engineering, and model training pipelines using Spark, MLflow, Databricks, and big‑data ecosystems
Partner with product, engineering, and clinical domain teams to translate complex business challenges into scalable ML and GenAI solutions
Optimize and monitor ML models in production, ensuring accuracy, latency, compliance, and responsible‑AI best practices
Present AI/ML solution designs, model insights, and GenAI architecture recommendations to technical and non‑technical stakeholders
Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI
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
Bachelor's degree in CS or IT related field
5+ years of hands‑on experience in AI/ML engineering, deep learning, or applied machine learning
3+ years of experience in Python, PySpark, ML frameworks (TensorFlow, PyTorch), and distributed training
3+ years of experience with big‑data systems (like Hadoop, Spark, Hive) and cloud platforms (like Azure, AWS, GCP)
2+ years of experience with LLMs, including:
Finetuning (LoRA, QLoRA, PEFT, SFT, or RLHF)
Prompt engineering & system design
RAG pipelines & vector search Preferred Qualifications
Prior experience with US healthcare datasets (claims, clinical, EMR/EHR, provider networks, payer ops)
Experience deploying ML/LLM workloads using Databricks, MLflow, Kubernetes, or serverless inference
Familiarity with modern GenAI tooling (LangChain, LlamaIndex, HuggingFace, OpenAI/Anthropic/Azure‑OpenAI APIs)
Knowledge of deep learning architectures (Transformers, sequence models, contrastive learning)
Experience optimizing model inference using quantization, distillation, or distributed GPU compute
Demonstrated success in AI product delivery, cross‑functional collaboration, and influencing technical strategy
Strong grounding in ML fundamentals (feature engineering, model evaluation, A/B testing, MLOps best practices)
All Telecommuters 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 $60,200 to $107,400 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
#RPO #GREEN
We are the UHC Payment Integrity AI/ML Engineering Team, responsible for designing and deploying advanced Machine Learning and Generative AI solutions that prevent Fraud, Waste, and Abuse (FWA) across the healthcare claims ecosystem.
Our work spans pre‑payment prediction, post‑payment anomaly detection, intelligent automation, and next‑generation LLM‑based decisioning.
The team is a blend of AI/ML engineers, data scientists, data engineers, and GenAI specialists who collaborate to build and scale end‑to‑end ML systems. We align closely with the organization's mission of improving affordability, operational efficiency, and trust in healthcare data
You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges.
Primary Responsibilities
Design, train, finetune, and deploy Large Language Models (LLMs) and Generative AI components for claims automation, anomaly detection, and investigative workflows
Build and operationalize ML pipelines using Python, PySpark, and cloud-native architectures (Azure/AWS/GCP)
Develop traditional machine learning models (classification, anomaly detection, NLP pipelines) for high‑volume healthcare datasets
Implement RAG (Retrieval‑Augmented Generation) systems, embedding models, and vector database integrations
Develop automated data processing, feature engineering, and model training pipelines using Spark, MLflow, Databricks, and big‑data ecosystems
Partner with product, engineering, and clinical domain teams to translate complex business challenges into scalable ML and GenAI solutions
Optimize and monitor ML models in production, ensuring accuracy, latency, compliance, and responsible‑AI best practices
Present AI/ML solution designs, model insights, and GenAI architecture recommendations to technical and non‑technical stakeholders
Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI
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
Bachelor's degree in CS or IT related field
5+ years of hands‑on experience in AI/ML engineering, deep learning, or applied machine learning
3+ years of experience in Python, PySpark, ML frameworks (TensorFlow, PyTorch), and distributed training
3+ years of experience with big‑data systems (like Hadoop, Spark, Hive) and cloud platforms (like Azure, AWS, GCP)
2+ years of experience with LLMs, including:
Finetuning (LoRA, QLoRA, PEFT, SFT, or RLHF)
Prompt engineering & system design
RAG pipelines & vector search Preferred Qualifications
Prior experience with US healthcare datasets (claims, clinical, EMR/EHR, provider networks, payer ops)
Experience deploying ML/LLM workloads using Databricks, MLflow, Kubernetes, or serverless inference
Familiarity with modern GenAI tooling (LangChain, LlamaIndex, HuggingFace, OpenAI/Anthropic/Azure‑OpenAI APIs)
Knowledge of deep learning architectures (Transformers, sequence models, contrastive learning)
Experience optimizing model inference using quantization, distillation, or distributed GPU compute
Demonstrated success in AI product delivery, cross‑functional collaboration, and influencing technical strategy
Strong grounding in ML fundamentals (feature engineering, model evaluation, A/B testing, MLOps best practices)
All Telecommuters 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 $60,200 to $107,400 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
#RPO #GREEN