Computational Data Scientist (PhD Candidate) with 5+ years of experience in computational modeling and integrative data analysis of complex biological systems. Proven collaborator in interdisciplinary Agile (Scrum) teams of scientists and clinicians, skilled at translating complex data into biologically relevant insights. Expert in applying advanced statistical models (Bayesian, Stochastic) to complex, multidimensional datasets. Fluent in R, Julia, and SQL.
Hi, I’m
Houda Yaqine
Computational Data Scientist
Bielefeld
Summary
Overview
8
years of professional experience
2
Certifications
3
Languages
Work History
Data Science Chair, Bielefeld University
Research Associate
03.2019 - Current
Job overview
- Integrative Data Analysis: Analyzed a large-scale, 115k-patient relational database (OMOP standard) to identify disease signatures and predict disease progression. Used SQL and Python (Pandas) to process, clean, and feature-engineer complex, multidimensional patient data.
- Model Validation: Built a novel Bayesian model (R) to estimate classifier (ROC) performance and diagnostic accuracy in the absence of gold-standard data, a common problem in medical diagnostics.
- Interdisciplinary Collaboration: Worked closely with an interdisciplinary team (statisticians, engineers, and clinicians) using Agile (Scrum) methodologies to manage project goals, track deliverables against timelines, and communicate results.
- Data Strategy & Optimization: Developed Optimal Experimental Design (DoE) models (Python, Julia) for dynamic (ODE) systems to optimize data collection timing. This approach aimed to reduce animal sacrifice by identifying the most informative data points for high parameter precision and prediction accuracy, after first validating the model against pilot data.
- Advanced Forecasting: Designed and implemented stochastic (SDE) and Markov Jump Process models in Julia for "what-if" policy and scenario simulations for epidemic forecasting.
- Decision & Cost Analysis: Applied Value of Information (VoI) frameworks to assess the economic value of new data collection, supporting strategic decisions and cost-benefit analysis in water quality management.
- Research & Grant Proposals: Assisted in the development and writing of new research proposals to secure project funding.
University of Malaga
Modeling Research Associate
10.2017 - 07.2018
Job overview
- Computational Biology & Modeling: Developed and analyzed mechanistic models (dynamic systems) of breast cancer progression by modeling specific protein markers and disease pathways.
Education
Sultan Moulay Slimane UniversityBeni Mellal, Morocco
Master of Science from Applied Mathematics
04.2001
University Overview
- Completed Coursework: Approximation of Partial Differential Equations (PDE), Optimal Control, Optimization
Sultan Moulay Slimane UniversityBeni Mellal, Morocco
Bachelor of Science from Mathematics And Computer Science
04.2001
University Overview
- Completed Coursework: Object-Oriented Programming (Java), C, SQL
Skills
Accomplishments
Accomplishments
- Honorable Mention, Best Poster Award | DagStat (2025)
- Travel Grant | Hausdorff Centre of Mathematics (2022)
- "Challenges for Women in Mathematics" Grant | Technical University of Munich (2018)
- One Year Research Scholarship | Women for Africa Foundation (2017)
Certification
Experimental Design and Analysis of Data from Animal Experiments Instituto de Investigação e Inovação em Saúdei3S, Porto, Portugal
Timeline
Introduction to Good Clinical Practice Novartis
09-2025
Experimental Design and Analysis of Data from Animal Experiments Instituto de Investigação e Inovação em Saúdei3S, Porto, Portugal
12-2023
Research Associate
Data Science Chair, Bielefeld University
03.2019 - Current
Modeling Research Associate
University of Malaga
10.2017 - 07.2018
Sultan Moulay Slimane University
Master of Science from Applied Mathematics
04.2001
Sultan Moulay Slimane University
Bachelor of Science from Mathematics And Computer Science
04.2001