process mining , Deep Learning, Nlp, Spark, Databricks, Python, data pipelines, unsupervised ML, ML models, supervised ML

Azure Databricks, Tensorflow, Pytorch, MLops, Python, LangChain, LLM application development, reinforcement learning, CNNs, prompt engineering, LangGraph, enterprise AI security, RAG, NLP techniques, Vision Transformers, Transformer architectures

Hadoop, Natural Language Processing, Sql, Tensorflow, Pytorch, Gcp, MLops, Docker, Spark, Keras, Azure, Python, Kubernetes, AWS, LangChain, DSPy

causal inference , prophet , Sql, Tensorflow, Pytorch, MLops, Databricks, Python, Airflow, data pipelines, scikit-learn, PyMC, Stan, Bayesian modeling, R, dbt, Experimental Design, hierarchical models, feature engineering

Machine Learning, Nlp, Data Mining, Apache Spark, Information Retrieval, Python, Deep Learning, Statistics

matching , Sql, Statistical Modelling, Pyspark, BigQuery, Python, data quality checks, feature engineering, GenAI, reusable analytics datasets, orchestration frameworks, embeddings, agentic automation, enterprise ML data tooling, model scoring processes, retrieval augmented generation, anomaly detection, Optimization, vector databases, Regression, data pipelines, Classification, distributed compute, large-scale data processing, model evaluation, dbt, cloud data platforms, model monitoring, prompt engineering, Forecasting

Sql, Nosql, Tensorflow, Numpy, Nltk, Pytorch, Pandas, Gcp, Docker, Azure, Python, AWS, LangChain, Generative AI, Hugging Face Transformers, Scikit-learn, MLflow, spaCy, NLP techniques

Machine Learning, Natural Language Processing, Python, Sql, Deep Learning, Model Evaluation

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

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