Scipy, Pyspark, Sql, Numpy, Pandas, XGBoost, Python, hyper-parameter optimization, Visualization, Data Processing, Amazon Quick Sight, object-oriented programming, code versioning with Git, CI CD, Scikit-Learn, model validation, test-driven development, AWS SageMaker, transformation pipeline development, data ingestion, feature selection

probability , statistical concepts , Tableau, Sql, Clustering, Python, Sap Business Objects, regressions, Looker, R-Shiny, R, Microstrategy

Machine Learning, Artificial Intelligence, Data Science, Data Quality, Generative AI, Cost Optimization, Retrieval-Augmented Generation, Technical Quality Bar Setting, AI Solution Design, Responsible AI Practices, Model Governance, AI Evaluation, Model Performance Monitoring, Enterprise AI Delivery, Large Language Models

Data Governance, Cybersecurity, digital infrastructure, AI regulation, online safety

Cybersecurity, Data Analytics, Manufacturing Analytics, ERP platforms, Industrial IoT, AI-enabled technologies

XGBoost, Advanced Sql, Class Weights, Airflow, SMOTE, SHAP, LightGBM, MLflow, Gradient Boosting frameworks, CatBoost, Scikit-Learn

model development , Mqtt, Hypothesis Testing, Amqp, Databricks, AWS, data pipelines, GenAI use cases, retrieval-augmented generation, robotics data formats, Data Collection, analytics layer, ML models, OPC-UA, data models, pipeline design, ingestion pipelines, backend services, robotics telemetry

causal inference , Sql, Python, difference-in-differences, MILP, uplift modelling, constrained optimisation, observational causal methods, optimising promotions, Lagrangian methods, synthetic control, instrumental variables, deep uplift architectures, propensity weighting, marketing incentives, heterogeneous treatment effect estimation, DR-learner, meta-learners, S T X R causal forests, Pricing

Orchestration, Sql, Nlp, Spark, Python, feature stores, LLMs, AI Agents, Time-series, Semantic Layer, MLflow, ML stack, anomaly detection, vector DBs, RAG, Recommenders, Knowledge Graphs