At PwC, I scope business problems with stakeholders and deliver statistical, machine learning, and AI solutions for clients in finance, telecom, and recycling and EPR.
I design classification and regression models, and apply LLMs to classification, extraction, and intelligent document processing. I also built reusable Python frameworks for data preparation, model training, and evaluation.
My work includes time series forecasting with backtesting and drift detection, as well as experiments and hypothesis tests to quantify impact. I source data from warehouses, SAP ERP, APIs, and files, then deliver reporting in Power BI, Tableau, and Looker.
At Yamex, I built and evaluated machine learning models and a RAG-based knowledge assistant using LangChain and vector databases. I also developed Python and SQL data pipelines and created a project using TensorFlow and PyTorch to classify plant species from images.
