causal inference , Hadoop, Power Bi, Tableau, Clustering, Sql, Hive, Spark, Statistical Inference, Python, Regression, unsupervised machine learning, Classification, Statistical Modeling, Experimental Design

data engineering , Large Language Models (LLMs), Machine Learning, Sql, Deep Learning, Tensorflow, Numpy, Pandas, Azure, Python, AWS, Agile SDLC, scikit-learn, Data Pipelines, Relational Databases, Cloud-based Data Architecture

software engineering practices , Tensorflow, Devops, Pandas, Deep Learning, Pytorch, Version Control, Neural Networks, Machine Learning Algorithms, Keras, Data Integration, Agile Methodologies, Decision Trees, Numpy, Python, Apis, scikit-learn, LLMs, Bayesian techniques, population-based meta-heuristic optimization methods, GenAI, ensemble methods, statistical analysis techniques, ML Ops practices, Regression, Classification, validation methods, time-series, Data and Cloud environments

regression models , snowflake , Power Bi, Tableau, Redshift, Sql, Quicksight, Time Series Analysis, Decision Trees, Spark, Databricks, Azure, Python, AWS, Gradient Boosting Models, Clustering and Segmentation, Random Forests, Recommendation Systems, Customer Propensity Modeling

Hadoop, Data Security, Data Quality, Data Governance, Clustering, Sql, Metadata Management, Spark, Predictive Modeling, Python, LLMs, Iceberg, Superset, Classification techniques, Knowledge graph

Machine Learning, Python, MLops, Retrieval-Augmented Generation, Fine-Tuning, Large Language Models, Prompt Engineering, GenAI

Python, Sql

Sql, Natural Language Processing, Tensorflow, Tableau, Azure Machine Learning, Deep Learning, Power Bi, Pytorch, Python, AWS Quicksight, AWS Sagemaker, R

Sql, Python, Data Analytics, Machine Learning, Feature Engineering, Predictive Models, Decisioning Logic

statistical model , Machine Learning, Python, Sql, Mathematical Skills