• Provide advanced analytical, machine learning, and data engineering support. • Design, develop, and deploy machine learning models for classification, regression, time series forecasting, and natural language processing applications. • Build and optimize automated, scalable ETL/ELT pipelines using Python, SQL, and cloud-based tools. • Develop and maintain production ML systems including model deployment, monitoring, versioning, and performance tracking. • Design, develop, and deploy interactive dashboards and data visualizations. • Perform end-to-end model development including exploratory data analysis, feature engineering, hyperparameter tuning, model validation, and documentation. • Develop and maintain data pipelines and workflows using tools such as AWS services, Databricks, and GitLab CI/CD. • Conduct data mining, cleaning, and manipulation using SQL, Python (Pandas, NumPy), or R.