Spark, Java, Devops, Hadoop, Scala, Python, Etl, Relational Databases, ML algorithms, data management technology, cloud-based AI platforms, non-relational databases

snowflake , S3, Pyspark, AWS Glue, Kafka, Docker, Data Governance, Python, BigQuery, Collibra, Redshift, Sql, MLops, Spark, Kubernetes, Airflow, Purview, Alation, Great Expectations, MLflow, Feast, GitHub Actions, Apache Atlas, Vertex AI, Kubeflow, Evidently, DataHub, SageMaker, dbt, GCS

MLops, FastAPI, Python, AWS, LangChain, Open Source LLMs, Agent Architectures, LangGraph, SageMaker, GraphRAG, ComfyUI, RAG, Generative Content Pipelines, Gen3D, MCP, Gen2D, Stable Diffusion

Algorithms, Machine Learning, Data Structures, Python, Agent framework development, LLM fundamentals, RAG optimization, SFT for LLMs, RLHF

Java, Machine Learning, Data Mining, Deep Learning, Tensorflow, Pytorch, MLops, Pattern Recognition, Python, Random Forests, Model Training Pipelines, Recommendation Systems, Model Monitoring, Gradient Boosting Machines, Learning to Rank

SAS, Tableau, Sql, Python, sensitivity analysis, Segmentation, Model governance, Data analytics tools, AML Monitoring, R, model validation, Simulation, Enterprise-level AML monitoring systems, Statistical Techniques, Threshold tuning, Scenario design, Sampling methodology

Python Programming, Agile Project Management, Pytorch, LangChain, data visualization packages, boosting models, GenAI solutions, transformer models, AI applications

risk frameworks , Data Privacy, financial services regulatory requirements, senior management reporting, control assessments, technology risk guidelines, AI security risks, Cisa, model robustness, adversarial attacks, CRISC

Azure Databricks, XGBoost, Spark, Python, Etl, scikit-learn, governance frameworks, data quality validation, pipeline orchestration, model performance tracking, Production Monitoring, cloud data platforms, drift detection, feature engineering