Hey there!

I'm a data scientist with a strong background in statistics, machine learning, and causal inference, currently working at DenizBank, where I develop analytical solutions primarily for marketing purposes. My journey began in English Literature, but after coming across Robert Sapolsky's Behave, I became deeply curious about behavioral science. This curiosity led me to MINT Lab and, ultimately, to data analytics.

I’ve combined my expertise in analytics with my passion for sports, particularly basketball, where I’ve developed expected points models, interactive visualizations, and play-by-play tracking tools to analyze player performance and game dynamics. Beyond analytics, I enjoy teaching—I’ve led machine learning workshops, hosted webinars on basketball analytics, and created resources to teach statistics through simulations.

I also actively share insights on data science, statistics, and sports analytics through my blog. My posts explore topics like Bayesian statistics, inference, machine learning, model fitting, and the intersection of basketball analytics with real-world decision-making. I strive to make data science more accessible by breaking down complex concepts into intuitive explanations and providing Python and R code for readers to follow along.

You can explore my blog and learn more about me at: yigitasik.github.io