Product Analyst – AI/ML Focus at Intel

Collaborated with data scientists and ML engineers to refine anomaly detection and forecasting models using scikit-learn, XGBoost, and PyTorch, contributing to an 18% improvement in accuracy. Supported development of Python and SQL pipelines orchestrated with Airflow to prepare ML-ready datasets, helping reduce feature engineering time by 35%. Co-developed LLM-powered internal tools using LangChain, OpenAI GPT-4, embeddings, and vector search (FAISS) to automate reporting and research workflows, lowering manual effort by 25%. Assisted in building Power BI dashboards that monitor model performance, drift, and LLM usage metrics, improving issue resolution speed by 20%. Participated in A/B testing and experimentation to evaluate ML-driven recommendations and interface variants, contributing to a 15% increase in user conversions. Worked with product managers and AI teams to define requirements for scalable Generative AI features including RAG pipelines, prompt workflows, and model evaluati

AI Business Analyst at Alliance Technology Group

Led design and deployment of LLM-based reporting automation using Azure OpenAI and LangChain, saving 30+ hours/month. Engineered ETL pipelines on AWS (S3, Lambda, Glue) for preprocessing, validation, and automated retraining. Built MLflow and CI/CD workflows for versioning, experiment tracking, and automated retraining. Developed KPI dashboards and drift detection frameworks in Power BI, improving data quality checks by 22%. Worked with data scientists to fine-tune GPT models and optimize prompts, improving contextual accuracy by 28%.