Over Anna
Recent MSc graduate (Distinction) specializing in applied machine learning and statistical modeling. I help organizations build robust, interpretable ML solutions while ensuring ethical deployment and fairness across diverse applications.
What I Offer:
Machine Learning & AI Development
- End-to-end ML pipeline development and deployment, including data cleaning and visualisation
- Supervised and unsupervised learning implementations
- Natural Language Processing: text classification, sentiment analysis, entity recognition
- Model optimization and performance tuning
- Predictive modelling and classification problems
Statistical Analysis & Modelling
- Advanced statistical modelling (causal analysis, mediation analysis, Latent variable modelling)
- Hypothesis testing and experimental design
- Data visualization and insight generation
- A/B testing and results interpretation
Ethical AI & Model Governance
- Bias detection and mitigation strategies (AIF360)
- Model interpretability and explainability (SHAP, LIME)
- Fairness metrics implementation
- AI documentation and audit trails
- GDPR and AI Act compliance assessment
Technical Stack: Python (pandas, numpy, scikit-learn, seaborn, matplotlib) | R (tidyverse) | STATA, SPSS | TensorFlow | Keras | Hugging Face | NLP libraries
Domain Experience: Health informatics | Compliance systems | Process optimisation
Recent Impact:
- Developed ML methods comparison framework addressing ethical considerations
- Optimized data management systems reducing processing time by 50%
- Managed compliance data systems for 500+ companies
Based in Belgium with work authorisation. Available for projects across sectors requiring rigorous data analysis, machine learning implementation, and responsible AI practices.
Engels
Tweetalig / moedertaal
Frans
Tweetalig / moedertaal
Spaans
Beperkte professionele capaciteit
Nederlands
Basiskennis
Kan op locatie werken
Brussels (tot 50km)
Werkervaring
- King's College LondonMaster Research ProjectONDERZOEKSCENTRAseptember 2024 - oktober 2025 (1 jaar en 1 maand)London, Verenigd Koninkrijk• Design of a machine learning benchmarking project: evaluating ML methods for depression detection from speech against ethical criteria, directly addressing AI safety challenges in healthcare evaluation. [manuscript under publication]• Systematic comparison of five machine learning methods (SVM, Elastic Net, GMM, MLP, Random Forest) across three datasets and five languages, totalling 13k+ speech samples.• Evaluation of the 25 models across performance, interpretability, bias, and cross-language generalisability.Skills & Libraries: Python | Bias mitigation (AIF360) | Interpretability (LIME, SHAP) | Research Report | Data Cleaning
- King's College LondonCo-creator & Policy Placementseptember 2024 - september 2025 (1 jaar)London, UK• Member of collaborative policy research teams reviewing university policy on usage of student data, anti-racism, anti-bullying and entrepreneurship• Chosen from cohort to lead a four people group creating speculative prototypes and policy recommendations advising the data policy
- BurotelAdministrator & Project Manageroktober 2023 - mei 2024 (7 maanden)Brussels, Belgium• Project manager: optimised the daily tasks and data collection processes improving efficiency within the company, coordinating CEO expectations and the developper team• Project leader: created Excel records for over 500 client companies in accordance with Belgian anti-money laundering legislation with automatic email reminders• Managed administrative tasks: client queries, room bookings, post correspondence
Aanbevelingen
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Opleidingen
- MSc Applied Statistical Modelling & Health InformaticsKing's College London2025Thesis: “Beyond Accuracy: Challenges in Ethically Comparing Machine Learning Methods for Mental Disorder Detection.” [Manuscript publication in progress] Modules: Statistical Modelling (inc. causal & latent variable), AI Programming: Machine Learning, NLP, AI for health informatics
- EU Policy Making CertificateBrussels School of Governance, VUB2025Focus: EU governance and policy, AI & Digital Rights (AI Act, GDPR), Digital Competition, Sustainability