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 opportunities 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 environment. Healthcare experience is strongly preferred.
- Robust proficiency in:
- Databricks
- Python (Pandas, Scikit-learn, NumPy, TensorFlow, MLflow)
- SQL
- Strong 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 in at least one of the following:
- Classification
- Regression
- Time Series
- Recommendation Systems
- Agentic AI / LLMs / RAG
- Strong statistical modeling foundation with experience building production-quality ML systems.
- Preferred: Knowledge of US healthcare, particularly Revenue Cycle Management (RCM), including familiarity with EDI transactions such as 837 and 835.
- Ability to work effectively in a fast-paced environment involving rapid prototyping, ambiguity, and iterative delivery.
- Self-motivated and solution-oriented, with the ability to independently research, troubleshoot, and identify solutions to technical or data challenges.

📌 AIML + Databricks (Hyderabad)
🏢 Prophecy Technologies
📍 Hyderabad