Kamen Radew
Chief Data & Information Officer @NeXtWind
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WORK HISTORY
Chief Data & Information Officer @NeXtWind
Berlin, DE
Foundation: Transitioning the company from \"a bunch of Microsoft Office documents in Microsoft SharePoint\" to \"a global Database and Application Platform with built-in AI capabilities.\"• Tactics: Creating the Digital Twin of the company, with full mapping between physical processes and their digital counterparts, allowing for 360-view and time-travelling capabilities.• Strategy: Driving a number of strategic initiatives, from discovering new business opportunities (co-location, extension, etc.) to unlocking new verticals (decentralized power production/consumption).
EDUCATION
Polish Academy of Sciences
Doctor of Philosophy - PhD, Data Science and Machine Learning
Warsaw University of Technology
Master of Science - MS, Mathematics and Statistics
SKILLS
ABOUT KAMEN RADEW
Seasoned Data Leader with more than two decades of professional, hands-on experience across the full data stack - from engineering and science to strategy and consulting. I have built scalable platforms, designed AI/ML solutions, and delivered data-driven digital transformations in sectors like energy, finance, telco, logistics, and healthcare.As a people-first leader, I have been responsible for teams ranging from 25 to 100+ people, growing high-performing data organizations at PwC, Teradata, and HelloFresh. I focus on team development, a trust-based approach, cross-functional collaboration, and always driving business outcomes from business realities.I specialize in projects that create measurable impact - from predictive maintenance and dynamic pricing to operational optimization. My focus is on using information technology to advance the most important verticals for our civilization: Precision Medicine, FoodTech, Renewable Energy and democratizing access to Knowledge.“Let the dataset change your mindset.” — Hans Rosling• Specialties Data Science Statistics (Frequentist + Bayesian) Machine Learning Artificial Intelligence• Languages Python R SQL Stan Julia C++ C Bash JSON YAML Markdown LaTeX• Libraries Dask + pandas + scikit-learn + FastAPI + Streamlit tidyverse + tidymodels + Plumber + Shiny• Environments Databricks JupyterHub + JupyterLab RStudio Server / Workbench Visual Studio Code• Big Data Delta Lake Spark (+ SQL + Structured Streaming + ML) Flink Kafka Presto / Trino dbt• Deep Learning Keras + TensorFlow + TensorFlow Probability fast.ai + PyTorch + Pyro Horovod• Ensemble Learning Bagging (Random Forest) Boosting (CatBoost + LightGBM + XGBoost) Stacking• DevOps GitLab Gitpod Vagrant Terraform Pulumi Ansible Buildah / Podman Docker K8s• MLOps DVC Argo Prefect Airflow Kubeflow Metaflow MLflow Optuna Hyperopt Seldon
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