data wrangling , containerization , Apis, Gcp, Docker, Azure, Python, AWS, data pipelines, LLMs, cloud platforms, governance frameworks, Monitoring, ML models, model integration, model explainability, RAG, AI agents, bias mitigation, feature engineering, Deployment, responsible AI practices

data engineering , Machine Learning, Cloud Technologies, Generative AI, Agentic AI, LLMs, modern data platforms, AI agent frameworks, RAG architectures

S3, Machine Learning, Spark, Cloudera, Tableau, Sql, Python, Generative AI, predictive models, Large Language models, Dify

data preparation , Azure Synapse, Predictive Modelling, Python, Sql, Statistics, Microsoft Fabric, Feature engineering, Model evaluation

Devops, Spark, Gitlab, Databricks, Azure, Python, Sql, AWS, R, ModelOps

Python, Sql, churn prediction, reporting frameworks, propensity to buy, DTC data structures, Segmentation

Sql, Python, Angular, Statistical Tools, Dash, Plotly, Data visualization tools

Tensorflow, Numpy, Machine Learning, Scipy, Pandas, Pytorch, Microsoft Azure, Digital Signal Processing, Python, Deep Learning, scikit-learn

Machine Learning, Apache Spark, Nlp, Docker, Statistical Analysis, Kubernetes, Python, Feature Engineering, R, LLMs for GenAI or Agentic AI