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Tier-1 brand, metro, popular mid-level ML role, broad required skillset and cloud experience amplify competition.
Core ML/LLM skills transfer, but healthcare domain, compliance and claims experience increase specificity.
Explicit 3+ years and mandatory cloud, ML frameworks, big data, and degree requirements tighten filtering.
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Design, develop, and deploy ML, AI, and Generative AI solutions to address complex healthcare and provider business problems.
Analyze large-scale structured and unstructured data to generate actionable insights and improve platform intelligence through predictive models, NLP, and LLM-powered applications.
Collaborate with cross-functional teams to translate requirements into data-driven solutions, develop data pipelines, ensure data quality and compliance, and continuously improve model performance in production.
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field.
3+ years experience in Data Science, Machine Learning, Advanced Analytics, or AI/ML solution development.
Proficiency with cloud platforms (Azure/AWS), big data technologies (Spark/Hadoop), Python, SQL, statistical analysis, ML algorithms, and AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Work Experience Required: Minimum 3 years in relevant fields.
Experience working in healthcare, provider, claims, or enterprise data domains is preferred.
Familiarity with Generative AI, Large Language Models, and certifications such as Microsoft Azure AI Engineer, Databricks Data Scientist, or AWS ML Specialty increase competitiveness.
Ability to translate complex business challenges into data-driven solutions and communicate insights effectively to stakeholders.