Natural Language Processing, Power Bi, Tableau, Sql, Tensorflow, Deep Learning, Git, Pytorch, Spark, Databricks, Azure, Python, AWS, data pipeline development, LLM Agentic AI, scikit-learn, machine learning frameworks, DevOps practices, R, ETL processes

Gcp, MLops, Docker, Gitlab, Databricks, Azure, Kubernetes, Python, AWS, LangChain, LLaMA, vector databases, MLflow, Anthropic, Pinecone, LangGraph, Deep Learning Frameworks, FAISS, NLP techniques, OpenAI, Generative AI models, Weaviate

Numpy, Pandas, Docker, Postgres, Flask, FastAPI, Python, Redis

causal inference , Machine Learning, Hadoop, Sql, Hive, MLops, Spark, Python, Generative AI, Model Evaluation, Optimization, Statistical Measurement, Operations Research, AI Engineering, Data Analysis, Simulation

Power Bi, Machine Learning, Tableau, Python, Data science libraries, Statistical Modeling, Data Analysis, R

Natural Language Processing, Performance Tuning, Sql, Deep Learning, Tensorflow, Computer Vision, Pytorch, Python, fine-tuning, Transformers, generative AI, transfer learning, model deployment, temporal GANs, multimodal learning, training large-scale models, ML evaluation techniques, diffusion models

graph databases , Data Modeling, Sparql, Python, Neo4j, Rdf, Elasticsearch, ontology design, Cypher, hierarchical taxonomies, graph systems, owl, JSON-LD, knowledge graph population, Elasticsearch DSL, Knowledge Representation, entity resolution, Gremlin, Neptune, data modeling skills, entity-relationship design

Pandas, Sklearn, Github, Numpy, AWS, Python, Azure, Gcp, Pytorch, LLMs, Transformers, monitoring logging and observability tools, Hugging Face, LLM evaluations, ML libraries, Monitoring, LangChain, RAG, CI CD pipelines, prompt engineering, automated testing strategies

Numpy, Sql, Keras, Java, Pandas, Pytorch, Python, Docker, Javascript, scikit-learn, Langchain, RAG, OpenAI API

Python, Sql, Bayesian causal modeling, R, uplift modeling, cloud-based data platforms, regression-based models, causal inference techniques