Über Kevin
I bridge the gap between complex research and functional software.
I bridge the gap between complex research and functional software. While many can build models, I specialise in pioneering data solutions in highly specialised domains -from Biotech and AgTech to FinTech.
I don't just apply algorithms; I build the scripts, tools, and cloud-integrated engines required to turn an idea into a product. My background is rooted in deep technical research, backed by a patent and peer-reviewed publications.
How I add value to your project
- Custom ML Architecture: I design and deploy end-to-end models, ensuring they integrate seamlessly into your environment.
- Automated Intelligence (NLP): I build text-mining tools to extract entities and patterns from unstructured data and scientific publications.
- Computer Vision & Monitoring: I develop software for visual data analysis, such as phenotyping, drought detection, and geometric pattern recognition.
- Feasibility Testing (PoC): I run high-speed experiments to prove a technology's viability before you commit to full-scale investment.
- Technical Leadership: I lead international teams to align AI constraints with business goals and ROI.
Proven Cross-Domain Success
- Life Sciences: Developed computational methods for HIV genomics and protein crystal structure analysis.
- AgTech: Designed instruments and software for crop stress monitoring and seed germination.
- Text Mining: Built systems for automated protein entity recognition from biomedical literature.
- Risk Systems: Architected cloud-based engines for automated decisions-making and predictive analytics.
Technical Stack
- Languages: R (Expert), Shell Scripting, SQL, Python, Java.
- AI/ML: Machine Learning, NLP, Computer Vision.
- Tools: MLOps.
Looking for a technical partner to turn your data into a working product? Let's schedule a brief intro call.
Englisch
Muttersprachlich oder zweisprachig
Deutsch
Muttersprachlich oder zweisprachig
Nur remote
Führt Projekte hauptsächlich remote aus
Projekt- und Berufserfahrung
- INFORM GmbH - Optimization SoftwareTeam Lead Shared Consulting ServicesBANKEN & VERSICHERUNGENJanuar 2023 - Heute (3 Jahre und 5 Monate)Aachen, Deutschland
- Smart Claim Management: To solve the problem of slow and manual insurance workflows, I developed an automated AI strategy by aligning user needs with technical constraints in Azure, using explainable models (tree-based models combined with TreeInterpreter algorithm) to achieve faster processing, and better business-tech alignment.
- Privacy-Preserving Fraud Detection: To address strict data privacy laws blocking model training, I created a decentralised detection system using a propitiatory software, H2O.ai, xgboost, R, and PMML to train models without moving raw data, achieving 100% privacy-compliant fraud detection.
- Real-Time Risk Infrastructure: To address the lack of risk model-assisted real-time processing, I architected a live decision engine where data were extracted via cloud-based tools and processed using proprietary feature engineering software. I developed and containerised the machine learning trainings within Docker, ultimately deploying them as PMML files through proprietary software to enable real-time, automated fraud decisions at scale.
- INFORM GmbH - Optimization SoftwareData Scientist / IT ConsultantBANKEN & VERSICHERUNGENApril 2018 - Dezember 2022 (4 Jahre und 8 Monate)Aachen, Deutschland
- Fraud Detection Proof-of-Concept: To reduce the high investment risk of new ML projects, I provided low-cost pilot validation by testing anomaly detection on banking data using Isolation Forest, G means clustering, Random Forest, Gradient Boosting Machine, XGBoost, and Explainable Boosting Machine, which confirmed ROI before a full-scale rollout.
- Customer Defaulter Prediction: To prevent financial losses from unpaid bills, I built an early-warning system by training classification algorithms in R on customer behaviour data, identifying potential defaults before they occurred.
- LemnaTecApplication ScientistBIOTECHNOLOGIEJanuar 2014 - März 2018 (4 Jahre und 2 Monate)Aachen, Deutschland
- Automated Plant Phenotyping: To replace subjective and slow manual monitoring, I created a visual monitoring instrument using a proprietary product solution based on OpenCV for data extraction, providing researchers with high-accuracy, objective data.
- Crop Stress Detection: To help researchers identify early signs of crop failure, I developed a visual extraction workflow using a proprietary production solution based on OpenCV to quantify phenotype dynamics, resulting in objective data for cereal resilience studies.
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Ausbildung und Abschlüsse
- PhD, Biological SciencesUniversity of Cambridge2010Thesis: Functional annotation of predicted active sites - PDB and literature mining. Research domain: Biomedical Literature Mining, Data Integration, Protein Structure Data Mining, and Bioinformatics.
- MSc BioinformaticsCranfield University2003Thesis: Novel protein structure prediction method - utilisation of a peptide conformation library derived from non-parametric statistical analysis. Courses: Bioinformatics, statistics, macromolecular modelling and analytical science.