Role Overview: We are seeking an experienced Data Scientist with strong expertise in Machine Learning, Python, SQL, Microsoft Fabric, and Azure-based data platforms. The ideal candidate will be responsible for designing, developing, deploying, and monitoring scalable ML solutions while collaborating with cross-functional teams.

Key Responsibilities:

• Perform Exploratory Data Analysis (EDA) to understand data patterns, distributions, anomalies, and quality issues.
• Work with Microsoft Fabric and SQL endpoints to prepare datasets for model training and prediction.
• Perform data cleaning, preprocessing, missing value handling, normalization, scaling, and outlier treatment.
• Handle imbalanced datasets using techniques such as SMOTE, oversampling, and resampling.
• Design and implement feature engineering and feature selection techniques.
• Manage features using Feast or similar feature store frameworks.
• Develop machine learning models using Decision Trees, Random Forest, LightGBM, and XGBoost.
• Apply ensemble learning techniques including bagging and boosting.
• Develop forecasting models and apply unsupervised learning techniques when required.
• Evaluate models using Accuracy, Precision, Recall, F1 Score, RMSE, and MAE.
• Perform cross-validation, hyperparameter tuning, and model optimization.
• Write clean, modular, and PEP8-compliant Python code.
• Build APIs using FastAPI or Flask for model inference.
• Develop and execute unit and integration tests for ML pipelines.
• Deploy machine learning models on Microsoft Fabric, Azure ML, and local environments.
• Monitor model performance, detect data drift, and support model retraining initiatives.
• Collaborate with Data Engineering and MLOps teams to productionize ML solutions.

Required Skills:

• Python
• SQL
• Microsoft Fabric
• Machine Learning
• Pandas
• NumPy
• Scikit-learn
• PyTorch
• PySpark
• XGBoost
• LightGBM
• FastAPI / Flask
• Feature Engineering
• Time Series Forecasting
• Model Evaluation & Optimization

Preferred Skills:

• Azure Machine Learning (Azure ML)
• Feast or Feature Store platforms
• MLOps practices and deployment frameworks
• CI/CD for ML applications

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• Strong experience in Python development and Machine Learning.
• Hands-on experience with Microsoft Fabric and advanced SQL querying.

Soft Skills:

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management skills.
• Ability to work effectively with cross-functional teams.