I’m a Data Scientist working on applied AI, product analytics, and decision-support systems.
My work focuses on building machine learning models, experiments, and analytics pipelines that help teams understand model behavior and make better decisions in real-world settings. I’ve worked across AI-driven products, healthcare systems, and large-scale data platforms.
- Applied machine learning and data science
- Product analytics, metrics, and experimentation
- LLM-based systems and recommender models
- Decision-support and analytics pipelines that ship to production
- Multimodal LLM Recommender Systems – combining text and image embeddings to study product recommendation performance at scale
- LLM-based Product Recommendation – fine-tuning and evaluating language models for next-item prediction
- Applied forecasting and pricing analytics – demand forecasting, elasticity modeling, and product analytics in production environments
- Healthcare analytics – decision-support models for financing, provider performance, and resource allocation
- Applied AI and generative models in products
- Experimentation and metrics beyond simple statistical significance
- How models behave in production and influence decisions
Most of my work is in Python and SQL, with applied ML tooling where it adds real value.
Feel free to explore the repos or reach out.