Responsibilities
• Develop machine learning, deep learning, and Generative AI models to support RCM use cases such as claim outcome prediction, denial classification, next-best-action recommendations, clinical appeal summarization, and workflow optimization.
• Build end-to-end ML pipelines, including feature engineering, model training, hyperparameter tuning, validation, and monitoring.
• Research and apply advanced techniques in LLMs, embeddings, Retrieval-Augmented Generation (RAG), prompt engineering, and document intelligence.
• Translate operational and product requirements into measurable model objectives, data specifications, and evaluation frameworks.
• Conduct Exploratory Data Analysis (EDA) to identify data patterns, anomalies, and business insights.
• Implement MLOps best practices, including model versioning, reproducibility, feature stores, and drift monitoring.
• Partner with Data Engineers to ensure feature availability, data quality, and scalable ML/AI deployment within Azure Databricks and enterprise platforms.




• Collaborate with cross-functional teams to communicate insights, present model results, and drive adoption of ML solutions.
• Stay updated on emerging AI technologies and propose enhancements or new prospects for Provider Engineering platforms.

Required Qualifications
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.
• 3–7+ years of hands-on experience developing ML/AI models in an applied industry setting. Healthcare experience is strongly preferred.
• Strong proficiency in:
• Databricks
• Python (Pandas, Scikit-learn, NumPy, TensorFlow, MLflow)
• SQL
• Solid working knowledge of GitHub Copilot or an equivalent enterprise-approved AI coding assistant.
• Experience working with Azure or similar cloud environments, preferably:
• Azure Databricks (MLflow, Delta Lake)
• Azure Machine Learning
• Azure Data Lake / Azure Data Factory
• Hands-on experience

📌 Aiml + Databricks Hyderabad
🏢 Prophecy Technologies
📍 Hyderabad