Grigorii Smirnov-pinchukov is a Data Scientist with 11 years of research and engineering experience, currently building internal ML and data-platform tooling at Heidelberg Materials to optimize cement production scheduling and increase renewable energy usage. He designs and maintains a Databricks-based demand forecasting pipeline whose predictions directly inform production timing to save costs and reduce carbon footprint. Trained as an astronomer with a Dr. rer. nat. from Universität Heidelberg and a research background at MPIA, he blends rigorous physical modeling, observational data reduction, and machine learning to accelerate scientific workflows. He has modernized legacy scientific codes, created Python interfaces, and deployed compute-heavy workloads on SLURM/MPI clusters, bridging research code and production systems. Based in Heidelberg, Germany, Grigorii brings both domain knowledge from astrophysics and practical data engineering skills to solve industrial decision-making problems. A less obvious strength is his experience translating complex scientific models into operational pipelines that deliver measurable business and sustainability impact.
11 years of coding experience
8 years of employment as a software developer
Dr. rer. nat., Astronomy, Magna cum laude, Dr. rer. nat., Astronomy, Magna cum laude at Universität Heidelberg
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