I’m a data science coach who’s big on making data feel simple and practical to drive business decision-making. I’ve done this work in real product and “messy data” settings through internships at Meta, Microsoft, and Pinterest, so I’m not just teaching theory, but I’m teaching what actually holds up when the data is unclear, the problem spec is ambiguous, and you still need to make a decision. Whether you’re trying to break into DS, level up for interviews, or ship a stronger project, I’ll meet you where you are: we’ll build your fundamentals (SQL, Python, stats, experimentation, modeling), then turn that into repeatable workflows for EDA, feature engineering, evaluation, and storytelling that makes sense to a PM or engineer. My style is hands-on and direct: we can debug your notebook together, refine a take-home or portfolio project, practice case studies, or tighten how you communicate tradeoffs (metrics, bias/variance, causality, fairness, uncertainty). You’ll get honest feedback, a plan that fits your time and resources, and a focus on understanding, not memorizing. The goal is that you leave each session with concrete progress and the confidence to explain your work clearly, end to end.