Mariia Bulycheva@mbulycheva

About me

I am an applied scientist with a strong background in machine learning, probabilistic modeling, and multimodal recommender systems. I hold a master's degree in mathematics—probability theory and statistics—and began my career in finance before transitioning into the tech industry. Currently, I focus on large-scale content personalization at Zalando, where I develop and evaluate machine learning models to optimize content ranking strategies. My work spans reinforcement learning, graph neural networks, and user engagement modeling, with an emphasis on long-term user interactions in recommender systems. I have led projects integrating advanced methodologies into production-scale systems and have contributed to research on applying graph-based models to recommendation tasks. Beyond recommendation systems, I have worked extensively in computer vision and time series forecasting, leveraging transformers for large-scale predictive modeling. My experience includes applying deep learning techniques to structured and unstructured data, optimizing performance in real-world applications, and scaling models efficiently to handle high-dimensional inputs.

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