Machine Learning, Pyspark, Knn, Sql, Python, Airflow, LightGBM, Gradient Boosting, Regression, Recommendation Systems, ranking, Classification, FAISS, Learning-to-Rank, CatBoost

Data Lineage, MLops, Algorithm selection, sensitivity analysis, AI Ethics Policy, Governance, Back-testing, Challenger model assessments, model validation, Feature engineering, Due Diligence, Audit-ready documentation, Model Risk Management

causal inference , GCP - BigQueryML, Sql, Tensorflow, Pytorch, Optimization Algorithms, XGBoost, Performance Monitoring, Linear Regression, Python, propensity modeling, feature engineering best practices, ROI, Gemini, scikit-learn, advanced experiment design, business impact modeling, Statistical Modeling, LTV, Vertex AI, model governance, incrementality, AWS SageMaker, MLOps orchestration tools, Experimental Design