Adam Dendek is a Senior Data Scientist and Ph.D. in High Energy Physics with 11 years of experience applying advanced ML and engineering to real-world problems across industry and research. He has led production-grade ML initiatives—from deploying one of the first real-time tracking models at LHCb to building few-shot and anomaly-detection systems for CPG receipt automation and precision agriculture yield prediction. Comfortable across the stack, he implements ETL and model pipelines with Airflow, PySpark, and scikit-learn, and prototypes deep learning with PyTorch, Siamese networks and GNNs. A practiced communicator and educator, he routinely translates complex results for stakeholders and has run machine learning training for global teams. Based in Poland, he blends rigorous scientific experimentation with pragmatic production engineering, often leveraging domain knowledge for creative data augmentation and model improvements.
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