Sanaz Raghib
Data Scientist with Neuroscience Background
Contacts
+31 684 344911
sanaz@dorost.nl LinkedIn
Summary
Experienced Data Scientist with 8+ years across academic, biotech, and healthcare domains, specializing in machine learning, statistical analysis, and healthcare data analytics. Skilled in designing analysis protocols, drafting study documentation, and communicating insights to interdisciplinary stakeholders. Proven track record of delivering solutions that reduce processing time by 30–70% and improve business outcomes. Currently returning from a brief career break after welcoming a new addition to my family.
Languages
Dutch Elementary
English Fluent
Turkish Native speaker
Azerbaijani Fluent
Persian Fluent
Education
Master

Interdisciplinary Neuroscience

Eskişehir Osmangazi University , 2016-09-01 — 2018-06-01
Bachelor

Anesthesia Technology

University of Tabriz , 2009-09-01 — 2013-06-01
Skills
Programming Languages
Master
Python, R, SQL
Machine Learning & AI
Master
Time Series Forecasting, Regression Analysis, Classification Models, Bayesian Statistics, Deep Learning
Data Science Tools
Master
NumPy, Pandas, Scikit-learn, PyTorch, Matplotlib, Seaborn, Jupyter Notebook
Business Intelligence
Intermediate
Power BI, Data Visualization, Dashboard Development, KPI Analysis
Development Tools
Intermediate
Git, Version Control, Collaborative Development
Laboratory & Research
Master
Cell Culture, iPSC/Organoids, CRISPR Gene Editing, Next-Generation Sequencing, Bioinformatics, Statistical Analysis
Healthcare Analytics & Research Methods
Intermediate
Healthcare Data Analysis, Protocol Development, Observational Studies, Statistical Reporting, Data Documentation
Awards
High Academic Performance
Eskişehir Osmangazi University
2018-06-01
Graduated with distinction (3.87/4.0 GPA) in Interdisciplinary Neuroscience
Data Scientist
BlueGen AI
2025-01-01 – 2025-05-01
Developed automated quality assessment systems for synthetic data generation, focusing on privacy-preserving metrics and client satisfaction optimization.
  • Automated synthetic data quality reporting pipeline, reducing evaluation time by 70%
  • Implemented privacy-preserving metrics that increased client acceptance rate by 25%
  • Collaborated with cross-functional teams using Python, Pandas, Scikit-learn, and PyTorch
  • Authored technical documentation and analysis protocols for data quality assessment frameworks
Junior Data Analyst
Neurolytics B.V.
2023-12-01 – 2024-06-01
Analyzed multi-client HR datasets to identify trends and develop predictive models for employee retention and workforce optimization.
  • Analyzed complex HR datasets across multiple clients, revealing key performance indicators that informed product roadmap decisions
  • Developed machine learning models for employee attrition prediction achieving 85% F1-score accuracy
  • Standardized Jupyter notebook reporting templates, reducing ad-hoc analysis time by 40%
  • Developed reproducible analytical workflows and comprehensive documentation for multi-client data studies
Trainee Data Analyst
Neuroship B.V.
2023-01-01 – 2023-12-01
Developed proof-of-concept forecasting models for SaaS marketplace demand prediction and implemented data processing pipelines.
  • Delivered demand forecasting proof-of-concept for SaaS marketplace with Mean Absolute Error < 5%
  • Cleaned and engineered features from 100,000+ rows of transactional data using advanced Pandas operations
  • Presented actionable insights to executive leadership, directly influencing pricing strategy updates
Research Technician
University of Amsterdam
2020-01-01 – 2022-05-01
Led advanced molecular biology workflows and developed bioinformatics pipelines for induced pluripotent stem cell research.
  • Managed NGS library preparation and CRISPR gene editing workflows on 50+ iPSC lines with 95% success rate
  • Developed R/Python bioinformatics pipelines that reduced variant calling turnaround time by 30%
  • Mentored and trained 4 junior researchers in advanced cell culture protocols and laboratory techniques
Guest Researcher
Radboud University Medical Center
2019-06-01 – 2019-09-01
Conducted electrophysiological experiments using patch-clamp techniques for neuroscience research.
  • Executed complex patch-clamp electrophysiology experiments, generating high-quality data for 2 conference presentations
Research Intern
University of Copenhagen
2018-07-01 – 2018-12-01
Developed disease models using patient-derived induced pluripotent stem cells for Alzheimer's research.
  • Generated patient-derived iPSC models for Alzheimer's disease research using advanced CRISPR gene editing techniques
Publications
ZNF91 is an endogenous repressor of the molecular phenotype associated with X-linked dystonia-parkinsonism (XDP)
2024-01-01
Proceedings of the National Academy of Sciences (PNAS)
Contributed to groundbreaking research on X-linked dystonia-parkinsonism, focusing on molecular mechanisms and therapeutic targets.