retrieval-augmented generation (RAG) pipelines, Customer Journey Analytics (CJA), Adobe Analytics, Sql, Numpy, Pandas, Databricks, Clustering, Python, experimentation design, statistical significance, statistical forecasting models, Powerpoint, a/b testing, cloud-based data lakehouse platforms, Regression, chatbots, prompt-engineered tools, AI agents, LLM-based applications

Sparql, Deep Learning, Tensorflow, Pytorch, Rdf, Python, AWS, Machine Learning, Google Cloud Platform, Sql, Databricks, Azure, scikit-learn, SHACL, enterprise ontologies, SAP Business Accelerator Hub, SAP Graph API, Cypher, Statistical Modeling, SKOS, SAP HANA Cloud, SAP Datasphere, GQL, owl, LLMs, generative AI, rdfs

Nlp, MLops, Deep Learning, ML AI pipelines, GenAI, LLM inference architectures, RAG systems, Agentic AI solutions, time series forecasting

Machine Learning, Artificial Intelligence, Python, Deep Learning, Cloud Platforms, Operations Research, Statistics, semantic analysis

SAS, Python, Statistical Analysis, R

causal inference , behavioral segmentation , Personalization, Unsupervised Learning, Sql, Python, LLMs, Segmentation, Agentic analytics, Ai, Statistics, a/b testing, Recommendation systems, Propensity modeling, Statistical Modeling, Experimental Design, experimentation, Causal measurement, Product analytics

containerization , Orchestration, Machine Learning, Hypothesis Testing, Tensorflow, Numpy, Pytorch, Python, Predictive Analytics, Sql, Deep Learning, Pandas, Spark, embeddings, vector databases, CI CD, model validation, MLOps practices, cloud-native ML platforms, distributed data processing frameworks, Statistical Modeling, probability statistics, semantic search, Generative AI, LLMs, Scikit-learn, prompt engineering, RAG, feature engineering, function calling

Sas Programming, SAS, Python, Statistical Analysis, R, Clinical SAS listings, statistical programming

probability , Tensorflow, Time Series Analysis, Pytorch, Azure ML, Microsoft Azure, aws, Machine Learning, Google Cloud Platform, Data Warehousing, XGBoost, MLops, Spark, python, Distributed Computing, databricks, Docker, Kubernetes, Sql, scikit-learn, mlflow, r, etl/elt pipelines, data lakes, retrieval-augmented generation, llms, agentic ai, Statistics, generative ai, Experimental Design