Large Language Models (LLMs), Machine Learning, Big Data Technologies, Deep Learning, Tensorflow, MLops, Pytorch, Python, Model monitoring, LLMOps, Model governance, Scikit-learn, Explainability, versioning, Agentic AI, Statistical Modeling, CI/CD, Responsible AI, Cost Optimization, Risk management

data preparation , Retrieval-Augmented Generation (RAG), Machine Learning, Deep Learning, Tensorflow, Nlp, Pytorch, Opencv, Python, Computer Vision, Generative AI, Agentic AI frameworks, LLMs, Statistical testing, Transformers, Quality assessment

prophet , Tensorflow, Numpy, Pandas, Pytorch, MLops, Machine Learning, Statistical Modelling, reinforcement learning, PyMC, Scikit-learn, Stan, GenAI applications, Time-series analysis, Foundation models, Python ecosystem

Loss Given Default (LGD), Probability of Default (PD), Exposure at Default (EAD), Sql, Numpy, Pandas, Statistical Modelling, Python, Logistic Regression, transition matrices, Data Analysis, scikit-learn, IFRS 9 ECL modelling, macroeconomic modelling, Survival Analysis, recovery analysis, statsmodels

Machine Learning, Python, Sql, R, Machine Learning Operation frameworks, Ai, Knowledge Graphs

Nlp, Pyspark, Databricks, Python, Sql, GenAI, observability monitoring, Applied Statistics, CI/CD, A/B test design, Large Language Models

Apis, Python, orchestration frameworks, Generative AI, LLMs, RAG vector databases, Claude, Responsible AI practices, prompt engineering, Agentic AI, enterprise integration patterns, Security, AI application development

resiliency , containerization , Java, Algorithms, Technical Leadership, Apis, Scalability, Distributed Systems, System Architecture, data structures, Python, object-oriented programming, DevOps practices, cloud-native applications, Mentoring, cloud platforms, software design principles, microservices architecture, AI-assisted development tools, performance optimization

Java, BigQuery, Hadoop, Kafka, Hive, MLops, Spark, Databricks, Python, Kubernetes, Airflow, HDFS, Delta Lake, CI/CD