Data Science, Machine Learning, Data Analysis, Data Processing

MLops, AWS, Terraform, Python, Agentic AI, LLMs

Machine Learning, Natural Language Processing, SAS, Sql, Deep Learning, Pandas, Hive, Numpy, Spark, Python, Generative AI, R

attribution modeling , Ml, Machine Learning, Pyspark, Neural Networks, Support Vector Machine, Clustering, Sql, Deep Learning, Databricks, Azure, Python, AWS, Ai, DL, Regression, Tree-based algorithms, Classification, Cloud Systems, Recommender System

Databricks, Sql, Tensorflow, Deep Learning, Machine Learning, Pytorch, Data Science, Gcp, Sparql, AWS, Python, Azure, cloud environments, semantic data systems, scikit-learn, GQL, semantic models, embeddings, enterprise ontologies, GenAI systems, RAG, semantic retrieval, Statistical Modeling, Cypher, applied AI, enterprise knowledge grounding, graph query languages, ML libraries, vector databases, knowledge engineering, big data infrastructure

snowflake , Sql, Tensorflow, Pandas, Pytorch, Spark, Python, Scikit-learn, vector databases, MLflow, prompt engineering, Agentic AI systems, MLOps practices, MCP Model Context Protocol, LLM-powered applications, Kubeflow, Generative AI LLM Proficiency, RAG pipelines

Data Science, Machine Learning, RDS, Power Bi, Artificial Intelligence, Pyspark, Redshift, Python, AWS

data engineering , Machine Learning, Tableau, Tensorflow, Numpy, Pytorch, Python, AWS, Time Series Analysis, Api Development, Sql, Git, Pandas, MLops, Gcp, Azure, Large Language Models, LangChain, Generative AI, LLMOps, Scikit-learn, Dataiku, LlamaIndex, ETL workflows

data engineering , Machine Learning, Python, Sql, Data Analysis, Causal AI, Structured Causal Models