S3, Pyspark, Docker, Terraform, Python, AWS, Cloudformation, Emr, Api Integration, Cloudwatch, Iam, Data Governance, Databricks, Airflow, model governance, data pipelines, MLflow, model registries, feature stores, real-time batch inference pipelines, ML Ops, Glue, Infrastructure-as-Code, compliance requirements

causal inference , Machine Learning, Spark, Python, Sql, Time Series Forecasting, AI solutions using LLMs and Agents, Regression, Simulation, Cloud-based platforms like Azure Databricks, Optimization

Machine Learning, Statistical Modelling, Python, Sql

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

Amazon Web Services, PostgreSQL, Artificial Intelligence, Tensorflow, Deep Learning, Confluence, Pytorch, Microsoft Azure, Python, Azure DevOps, Java, Machine Learning, Google Cloud Platform, Natural Language Processing, Jira, scikit-learn, Claude, GraphRAG, large language models, Generative AI, LLaMA, retrieval-augmented generation, FAISS, Milvus, OpenAI, Gemini

spatial data , Machine Learning, Python, Sql, Statistical Techniques

Pyspark, Tableau, Python, Sql, AWS, Data Analysis, Data pipeline development

Deep Learning, Nlp, Machine Learning, Pyspark, Python, Sql, generative AI, Ai

Deep Learning, Nlp, Predictive Modeling, Python, Generative AI, ML frameworks

Matplotlib, Machine Learning, Scipy, Git, Pandas, RDBMs, Docker, Spark, Clustering, Kubernetes, Python, Data Science methods, Azure stack, scikit-learn, Statistics, Bayesian regression, tree-based models, NumFOCUS stack