Kasia Kulma is a Data Science Champion and engineer with 10+ years of experience building production ML and data platforms across pharma, insurance, finance, aviation and environmental services. She combines hands-on data engineering (Databricks, Spark, ELT pipelines, Azure/AWS) with applied data science and MLOps, having reduced model lifecycle friction and cut deployment time through CI/CD and automation. Kasia has led teams and consultancy projects delivering scalable forecasting, optimisation and decision tools—one project sped an airport bag-flow model from two days to three minutes and another cut forecasting error from 23% to 5%. She runs Ibuki Data, contributes to open source around rstats and climate, mentors with R-Ladies, and blogs about data-for-good topics. With a PhD in Ecology and Evolutionary Biology, she brings rigorous experimental design and statistical thinking to industrial problems and an unusual depth in ecological and climate data.
10 years of coding experience
8 years of employment as a software developer
Biology and Chemistry, Biology and Chemistry at Liceum Ogolnoksztalcace nr 1 w Limanowej
Master's degree Biology/Biological Sciences General, Master's degree Biology/Biological Sciences General at Jagiellonian University
PhD Ecology and Evolutionary Biology, PhD Ecology and Evolutionary Biology at Uppsala University
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