Senior Machine Learning Engineer

Milliman

United States

United States

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About

Company Overview: At MedInsight, we prioritize Quality, Integrity, and Opportunity in every aspect of our business. As a trusted leader in healthcare intelligence, we strive to empower organizations to make informed decisions through our products and services. With over 300 healthcare organizations relying on our solutions, we are dedicated to improving patient outcomes while reducing waste. Our recognition as #1 for Payer Quality Analytics by clients in the Best in KLAS report for the last three years underscores our commitment to quality. As a subsidiary of Milliman, a global consultancy, we leverage a breadth of expertise in healthcare financing, data analytics, and business transformation. Position Summary: We are looking for a Senior Machine Learning Engineer with significant experience in healthcare claims and machine learning. Your role will involve designing, building, and deploying robust AI systems that enhance healthcare quality and drive insights in risk adjustment and population health. You will collaborate with various teams, including platform engineering, data science, product development, and clinical teams, to create impactful analytics products that utilize traditional machine learning, MLOps, and generative AI. What You'll Work On: MIKE (MedInsight Knowledge Engine) : Develop an AI assistant for healthcare analytics. Data Confidence Model (DCM) : Enhance our data validation and quality assurance processes with AI. Risk Adjustment AI : Automate HCC recapture and risk scoring through predictive modeling. Claims Analytics AI : Focus on pattern recognition, fraud detection, and usage forecasting. Population Health Models : Implement member segmentation and risk stratification through predictive analytics. Healthcare NLP : Work on clinical coding, documentation improvement, and insight extraction. Lakehouse AI Integration : Embed AI within our healthcare data platform. Primary Responsibilities: Design, build, and deploy production-grade ML models and MLOps pipelines. Create solutions that leverage healthcare claims data for risk prediction and population health. Implement scalable inference systems with thorough validation, monitoring, and performance tracking. Integrate large language models (LLMs) and generative AI into analytics products, focusing on RAG systems and conversational interfaces. Collaborate with engineering and clinical teams to devise AI solutions that meet business needs. Ensure model adherence to clinical accuracy, regulatory standards, and business trustworthiness. Contribute to the development of ML strategy, tools, and best practices throughout the organization. Requirements: Machine Learning & AI Expertise 5+ years of experience in ML engineering, including production deployments. Proficient in Python and familiar with libraries such as scikit-learn, XGBoost, PyTorch, and TensorFlow. Experience in supervised and unsupervised learning, feature engineering, model evaluation, and MLOps. Cloud ML platform experience (Azure ML, Databricks, SageMaker) and familiarity with containerization (Docker/Kubernetes). Knowledge of generative AI, large language models, prompt engineering, and RAG systems. Healthcare Analytics Experience 3+ years of experience working with healthcare claims data (medical, pharmacy, eligibility). Experience in population health analytics, risk adjustment metrics (CMS-HCC, HHS-HCC), and quality measures. Familiar with actuarial forecasting, cost trending, and healthcare operations. Collaboration & Communication Excellent at cross-functional collaboration with engineers, product managers, and clinical experts. Able to communicate technical concepts to non-technical stakeholders. Possess an ownership mentality, driving projects from concept to execution. Preferred Qualifications Advanced degree (MS/PhD) in Computer Science, Statistics, Applied Math, or a related field. Experience with healthcare analytics platforms (MedInsight, HealthEdge, Cotiviti). Knowledge of HEDIS, Star Ratings, and quality improvement programs. Experience in clinical NLP or medical coding. Understanding of HIPAA compliance and healthcare data security. Technical Environment Languages: Python, SQL, PySpark. ML Engineering: scikit-learn, XGBoost, PyTorch, TensorFlow, MLflow, Optuna. Generative AI: LangChain, OpenAI API, Azure OpenAI, HuggingFace, vector databases. Data Platforms: Azure Databricks, Azure Data Lake, PostgreSQL, Delta Lake. Cloud & MLOps: Azure ML, Azure DevOps, Docker, Kubernetes, CI/CD pipelines. Analytics: PowerBI, Jupyter, VS Code, Git. Location This role can be performed remotely within the United States. Compensation The salary range for this position is $104,900 - $199,065, based on location and experience. What makes this a great opportunity? Join a company that values your growth and wellbeing, offering a flexible work environment and a robust benefits package. Work in an innovative, fast-growing organization with abundant opportunities for advancement. Utilize your expertise to impact the future of MedInsight products and solutions directly. Benefits MedInsight provides a comprehensive benefits package, including: Medical, Dental, and Vision coverage for you and your family. Employee Assistance Program for personal and professional support. 401(k) Plan with employer matching and profit-sharing. Bonus opportunities based on performance. Flexible Spending Accounts for eligible expenses. Generous Paid Time Off (PTO) starting on your first day. A minimum of 10 paid holidays each year. Family-building benefits including adoption and fertility assistance. Paid parental leave for eligible employees. Life Insurance & AD&D fully covered by Milliman. Short-Term and Long-Term Disability fully covered by Milliman. Equal Opportunity We welcome applicants from all backgrounds and will not discriminate based on race, color, religion, sex, sexual orientation, national origin, disability, or status as a protected veteran. #LI-SM1 Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities. This employer is mandated to notify all applicants about their rights as per federal employment laws.

United States

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