Domain : Healthcare Predictive Analytics & Workforce Forecasting

Job Overview :

We are looking for experienced Machine Learning Engineers with strong expertise in Python, Machine Learning, Predictive Analytics, and Forecasting to develop and deploy end-to-end ML solutions.

Candidates should have hands-on experience with Microsoft Fabric Lakehouse and production-grade ML pipelines.

Key Responsibilities :

- Perform data exploration, cleaning, preprocessing, and feature engineering.

- Develop and deploy ML models for classification, prediction, and time-series forecasting.

- Build predictive models using XGBoost, Random Forest, and Scikit-learn.

- Implement model explainability using SHAP.

- Develop end-to-end ML pipelines covering training, validation, scoring, and deployment.

- Work with Microsoft Fabric Lakehouse, notebooks, and data pipelines.

- Monitor model performance, data quality, drift, and implement retraining processes.

- Integrate ML outputs with APIs and Power BI dashboards.

- Collaborate with Data Engineers, Architects, and BI teams.

Required Technical Skills :

- Strong Python, Pandas, NumPy, and SQL skills.

- Hands-on experience with Scikit-learn, XGBoost, Random Forest, and statistical modelling.

- Experience in classification, predictive analytics, and time-series forecasting.

- Strong knowledge of EDA, feature engineering, model evaluation, and hyperparameter tuning.

- Experience with SHAP and model explainability.

- Hands-on experience with Microsoft Fabric, Fabric Lakehouse, notebooks, and data pipelines.

- Experience in ML model deployment, monitoring, versioning, and retraining.

- Knowledge of MLOps practices and Power BI/API integration.

Candidate Expectations :

- 8 years of relevant AI/ML or Data Science experience.

- Proven experience developing and deploying end-to-end ML solutions.

- Ability to independently handle data preparation, model development, deployment, and monitoring.

- Strong analytical, problem-solving, and communication skills.

- Important: Practical ML model development and deployment experience is mandatory.

- Candidates must have hands-on exposure to Microsoft Fabric Lakehouse and working with Lakehouse data.

- Theoretical ML knowledge or data engineering-only experience will not be sufficient.