Sql, Data Science, Python, embeddings, knowledge engineering, enterprise ontologies, big data infrastructure, vector databases, semantic models, semantic retrieval, GenAI systems, enterprise knowledge grounding, RAG pipelines, semantic data systems, applied AI

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

Predictive Modeling, Machine Learning, Algorithm Design, Sql, Deep Learning, Tensorflow, Nlp, Pytorch, MLops, Spark, Python, a/b testing, AWS Bedrock, Data Pipelines, Scikit-learn, Statistical Methods, Recommendation Systems, GCP AI Platform, AWS SageMaker, Google Vertex AI, Uplift Modeling

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

Pyspark, Machine Learning, Data Mining, Excel, Python, Sql, AWS, R, Rspark, Statistical Pattern Recognition