Tableau, Sql, Python, experimental statistics

Machine Learning, Python, Sql, Deep Learning frameworks, Model Registries, Statistical Models, Feature Stores, Gradient Boosting

Matplotlib, Hadoop, Power Bi, Tableau, Sql, Tensorflow, Gcp, Pytorch, Spark, Azure, Python, AWS, Scikit-learn, R

Machine Learning, Software Development, Google Cloud Platform, Sql, Cloud solutions, Python, Data Analysis

Power Bi, Pyspark, Sql, Qlik, Time Series, Databricks, Python, LangChain, GenAI, Regression, Azure Services, Statistical Modeling, Classification, RAG

Drift detection (e.g. Evidently), PostgreSQL, Sql, Numpy, Pandas, Docker, XGBoost, Python, scikit-learn, LightGBM, CatBoost, Hyperparameter optimisation, SHAP, AWS-hosted infrastructure, Automated retraining pipelines, Feature engineering, Model evaluation

data engineering , Data Science, Machine Learning, MLOps principles and tools, AI applications, Statistical Modeling, Data platforms

simulations , text classification , MLops, Version Control, Sentiment Analysis, Testing, Nltk, Python, Docker, Summarization, Apis, Nlp, prediction, LLMs, operations research techniques, optimization heuristics, scikit-learn, text similarity, Hugging Face, model deployment, NER, agentic workflows, Optimization, topic modeling, feature extraction, text preprocessing, entity extraction, Classification, intent detection, traditional machine learning, spaCy