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From Food Labels to Reusable Ingredient Data
How our team built a traceable reference corpus and tested a human-in-the-loop workflow for linking Dutch food ingredients to FoodOn and ChEBI.
Hi, I'm Fabian Schreuder Data Scientist & Strategist
I blend machine learning, data engineering, and strategic analysis to solve complex problems in healthcare, sustainability, and business.
About Me
A data scientist with a passion for transforming complex data into actionable insights and robust data products. My expertise spans predictive modeling, big data engineering, and developing data-driven strategies, with a strong focus on ethical and responsible AI.
My Approach
I approach data science projects with a comprehensive methodology that combines statistical rigor, computational efficiency, and strategic foresight. My goal is to build solutions that are not only technically sound but also drive tangible value and positive outcomes.
1
Strategic Problem Definition2
Data Engineering & Processing3
Modeling & Validation4
Insight & DeploymentEducation
MSc Data Science for Food and Health
Specialization in Health & Sustainability Analytics
Wageningen University & Research • Sep 2024 - present
BSc Business and Consumer Sciences
Focus on Data Analytics & Consumer Behavior
Wageningen University & Research • 2022
Recent Projects
Healthcare Predictive Modeling
Built classification (CKD, PCOS) & survival models (cancer recurrence) using ML & advanced statistics.
Big Data Retail Analytics
Engineered a Spark-based system to analyze 70M+ transactions for cannibalization & basket size insights.
Sustainability Time Series Forecasting
Developed ARIMA & VAR models to forecast global food emissions from complex, multi-source data.
Personal Interests
Data Ethics & Responsible AI
Knowledge Graphs & Semantics
Big Data Systems
Data-Driven Strategy
Professional Journey
My career and educational path is defined by leading and executing impactful data projects at the intersection of industry and academia.
Sep 2024 - present
Master of Science - Data Science for Food and Health
Focus on Healthcare, Sustainability, and Big Data Analytics
Wageningen University & Research
Executed a diverse portfolio of data science projects, including building ML models for disease prediction (CKD, PCOS), developing survival models for cancer research (CRC), forecasting sustainability metrics with time series analysis (ARIMA, VAR), and constructing a healthcare knowledge graph using RDF and medical ontologies.
Apr 2024 - Sep 2024
Chat Flow Content & Performance Analyst
Foot Locker EMEA
Developed and maintained a Power BI dashboard to monitor chatbot performance across EMEA markets. Analyzed interaction data to identify trends, diagnose issues, and pinpoint areas for improvement in customer experience and deflection rates.
Power BI Data Analysis Dashboarding Business Intelligence Customer Experience
Key Achievements:
- Built comprehensive Power BI dashboard for KPI monitoring (deflection, escalations)
- Translated business needs into technical requirements and interactive visualizations
- Analyzed contact drivers to provide actionable insights for bot improvement
Oct 2022 - Apr 2024
CRM Strategist & Project Manager
Wageningen University & Research
Authored the strategic CRM plan to unify data systems and enable data-driven marketing. Led the subsequent CRM integration project, managing stakeholders, budget, and technical execution to create a unified customer view and enhance cross-selling capabilities.
CRM Strategy Project Management Data Integration Data Strategy Marketing Analytics
Key Achievements:
- Led a complex CRM integration project from planning to execution
- Developed a data strategy to de-silo systems and improve data quality
- Defined measurable business outcomes (ROI, conversion lift) for data projects
Oct 2022
Bachelor of Science - Business and Consumer Sciences
Focus on Data Analytics & Consumer Behavior
Wageningen University & Research
Developed a strong foundation in statistical analysis, research methodology, and business intelligence.
Technical Skills
My technical toolbox is built on a foundation of modern data science, engineering, and analytics technologies, allowing me to build robust, end-to-end data solutions.
Data Science & Machine Learning
Predictive Modeling (Classification & Regression) 95%
Time Series Forecasting (ARIMA, VAR) 90%
Survival Analysis (Cox Models) 85%
Unsupervised Learning (Clustering) 88%
Technologies & Tools
Python R Scikit-learn Pandas Statsmodels MICE pmdarima
Data Engineering & Big Data
Data Pipeline & ETL Development 92%
Knowledge Graphs (RDF, Ontologies) 85%
Big Data Processing 90%
Data Architecture (Lambda) 80%
Technologies & Tools
SQL Parquet RDFLib SNOMED-CT LOINC
Business Intelligence & Strategy
Power BI Dashboard Development 95%
Data-Driven Strategy (CRM) 90%
Data Ethics & Responsible AI 88%
Project Management 92%
Technologies & Tools
Power BI Power Query Data Visualization Stakeholder Management Risk Assessment
Additional Technical Skills
Programming Languages
- Python
- R
- SQL
Big Data Technologies
- Apache Spark
DevOps & Tools
- Git
- Docker
- Jupyter
- MLflow
Methodologies & Concepts
- Data Validation
- Measurement Error Correction
- MLOps
- AGILE
- Scrum
Explore My Data Science Articles & Projects
Dive into a portfolio of case studies showcasing my work in healthcare predictions, big data retail analytics, sustainability forecasting, CRM strategy, and ethical AI.
Featured Publication
Decoding the Dutch Diet: A Data-Driven Approach to Identifying National Meal Patterns
A deep dive into how I used Association Rule Mining and NLP-powered clustering on national survey data to identify popular Dutch dishes, analyze dietary trends over 15 years, and assess their nutritional quality.
When Should AI Ask About Your Meal?
For my MSc thesis, I built Snap and Say, a food logging app that uses photos, voice, and selective follow-up questions to balance nutritional detail with ease of use for older adults.
Navigating the Ethical Minefield of DTC Genetic Testing: A Framework for Responsible Innovation
The multi-billion dollar Direct-to-Consumer (DTC) genetic testing industry is an ethical minefield. This post breaks down the key risks—from data privacy to flawed health reports—and proposes a framework for responsible innovation using data justice and co-design principles.
Uncovering Dietary Patterns to Predict Colorectal Cancer Recurrence: A Data-Driven Approach
A case study on using Latent Profile Analysis and Cox Proportional Hazards modeling to identify pre-diagnosis dietary patterns associated with colorectal cancer recurrence. We navigated complex, high-dimensional health data to deliver clinically relevant insights.
Calibrating for Accuracy: Validating a Dietary Questionnaire with Linear Regression
A case study on validating a new Food Frequency Questionnaire (FFQ) for dietary fiber intake. This post details the use of 24-hour dietary recalls as a reference method and the application of linear regression calibration to correct for measurement error, enhancing data accuracy for epidemiological research.
Forecasting Global Food Production Emissions: A Time Series Case Study
Analyzed multi-source data on global food production, population, and emissions using time series techniques. Developed and compared forecasting models (ARIMA, VAR) to predict future trends.