Python Developer (Data Engineering & AI/ML)

Role Overview: You are a skilled Python Developer with strong SQL expertise and hands-on experience in AI and Machine Learning. Your main responsibility will be to work on data engineering, forecasting, and intelligent analytics solutions. This includes building data pipelines, feature engineering frameworks, machine learning and deep learning models, and integrating analytical outputs into dashboards and APIs. Exposure to .NET APIs is a plus, while PyTorch experience is mandatory for model development and experimentation. Key Responsibilities: - Develop and maintain Python-based ETL pipelines to extract data from multiple systems such as EMR, HRIS, Remittance, and Denial platforms - Perform data cleaning, normalization, and transformation for analytics use cases - Build feature engineering pipelines for productivity, backlog aging, inflow trends, and workforce analytics - Implement automated data validation and quality checks - Develop time-series forecasting models for inflow, capacity, and backlog prediction - Design, train, and tune machine learning models for prediction and classification tasks - Develop deep learning models using PyTorch (LSTM, GRU, sequence models, forecasting networks) - Implement probabilistic and ensemble modeling techniques to improve accuracy - Build scenario simulations and what-if analysis for staffing and productivity planning - Develop backend APIs (FastAPI / Flask) to expose model outputs to BI tools - Implement model retraining, monitoring, and performance tracking workflows - Support Human-in-the-Loop (HITL) validation processes - Collaborate with business SMEs, analysts, and engineering teams Qualification Required: - Bachelors degree in Computer Science / IT / Engineering or equivalent - 23 years of hands-on experience in Python development Role Overview: You are a skilled Python Developer with strong SQL expertise and hands-on experience in AI and Machine Learning. Your main responsibility will be to work on data engineering, forecasting, and intelligent analytics solutions. This includes building data pipelines, feature engineering frameworks, machine learning and deep learning models, and integrating analytical outputs into dashboards and APIs. Exposure to .NET APIs is a plus, while PyTorch experience is mandatory for model development and experimentation. Key Responsibilities: - Develop and maintain Python-based ETL pipelines to extract data from multiple systems such as EMR, HRIS, Remittance, and Denial platforms - Perform data cleaning, normalization, and transformation for analytics use cases - Build feature engineering pipelines for productivity, backlog aging, inflow trends, and workforce analytics - Implement automated data validation and quality checks - Develop time-series forecasting models for inflow, capacity, and backlog prediction - Design, train, and tune machine learning models for prediction and classification tasks - Develop deep learning models using PyTorch (LSTM, GRU, sequence models, forecasting networks) - Implement probabilistic and ensemble modeling techniques to improve accuracy - Build scenario simulations and what-if analysis for staffing and productivity planning - Develop backend APIs (FastAPI / Flask) to expose model outputs to BI tools - Implement model retraining, monitoring, and performance tracking workflows - Support Human-in-the-Loop (HITL) validation processes - Collaborate with business SMEs, analysts, and engineering teams Qualification Required: - Bachelors degree in Computer Science / IT / Engineering or equivalent - 23 years of hands-on experience in Python development