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Zaher KhraibaniZK

Zaher Khraibani

Senior Biostatistician (PhD) | AI Data Scientist

€600/day
Paris, FR
8-15 years
Machine learning
Data science
Big Data
Data analysis
Biostatistician

Average response time: 1 hour

Freelancer profile translated to English.
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About Zaher

**Senior Biostatistician (PhD in Biostatistics) with over 10 years of experience in clinical research, epidemiology, and data science applied to biomedical and public health data**. I act as a statistical expert and data scientist on projects with high scientific, clinical, and strategic impact, supporting pharmaceutical laboratories, biotechs, medtechs, CROs, startups in medical artificial intelligence, as well as academic and hospital teams in the design, analysis, and statistical valuation of their data-driven projects.


My areas of intervention include:
  • Statistical analysis of clinical trials (Phases I-IV)
  • Advanced survival analysis: Kaplan-Meier, Cox models, competing risks
  • Real-world data (RWD/RWE) exploitation
  • Statistical validation of artificial intelligence models in health
  • Predictive modeling and explainable machine learning
  • Development of reproducible pipelines (R, Python, SAS)
  • Scientific writing, protocols, Statistical Analysis Plan (SAP), Clinical Study Report (CSR)
  • Health-economic studies and budget impact analyses

I work on strategic projects with high clinical and regulatory impact: validation of diagnostic/prognostic AI tools, biomarker identification, study design optimization, survival analyses in oncology, rare diseases.

**My goal**: to transform complex data into reliable, interpretable, and actionable results for medical and business decision-making.
Public Sector
Biotechnologies
Pharmaceuticals
Health and Wellness
Software Publishing

  • French

    Native or bilingual

  • English

    Fluent

Can work on-site
Paris (up to 50km)

Experience

  • Owkin France
    Senior Biostatistician | AI in Healthcare & Oncology | MedTech & Biotech
    BIOTECH
    April 2025 - December 2025 (8 months)
    Paris, France
    Worked as a freelance senior biostatistician on multiple high-impact projects at Owkin, an AI-driven biotech company, contributing to clinical validation, analytical performance assessment, statistical modeling, and health-economic strategy for AI-based diagnostic and prognostic tools in oncology. Close collaboration with data science, medical, regulatory and product teams to ensure scientific robustness, regulatory readiness, and business relevance.
    • Clinical Statistics & Survival Analysis: Led advanced survival analyses on oncology cohorts: Kaplan–Meier estimation, Cox proportional hazards models, Hazard Ratios (HR), 95% confidence intervals, Wald & log-rank tests, Clinical validation of AI-based prognostic risk scores (low-risk vs high-risk stratification), Analysis of long-term clinical endpoints (dRFI, IDFS at 5 and 10 years), Interpretation of results for clinical study reports (CSR) and scientific communication, Contribution to scientific manuscripts and publication-ready analyses.
    • Analytical Validation & AI Model Performance: Statistical validation of AI models in digital pathology, Analytical performance studies including: Within-laboratory precision (WLP), Between-laboratory precision (BLP), Method comparison studies (e.g. H&E vs HES): Deming regression,Bias analysis,Bland–Altman plots, Definition of acceptance criteria, sample size estimation and validation protocols.
    • Statistical Programming & Reproducibility:Development of robust statistical pipelines in R,Automated analyses, reusable functions, and standardized reporting,Setup and maintenance of Git repositories to ensure:Code traceability,Version control,Full reproducibility, Clear documentation for internal knowledge transfer.
    • Health Economics, Pricing & Reimbursement Modeling: Design of economic models for AI medical devices:Fee-for-Service vs Bundled Payment systems,Cost-effectiveness and budget impact analysis.
    Survival Analysis Digital Pathology Clinical Validation AI in Healthcare Oncology
  • Scientific peer reviewer – Journal of the American Statistical Association (JASA).
    Senior Statistical Expert & Peer Reviewer
    RESEARCH
    October 2025 - Today (8 months)
    Paris, France
    Research article proposing a novel graph-theoretic, distribution-free test of randomness based on random interval graphs. The method detects complex dependencies (nonlinear, heteroskedastic, chaotic) beyond standard correlation tests and shows strong performance in simulations and real data applications.
    Statistical Computing Monte Carlo Simulation Statistical hypothesis testing Advanced statistical methods Time series analysis
  • Wiley – Cancer Medicine Journal
    Scientific Peer Reviewer – Oncology (Cancer Medicine, Wiley)
    RESEARCH
    April 2025 - Today (1 year and 2 months)
    Londres, United Kingdom
    Project: "Colorectal Peritoneal Metastasis Incidence and Survival in the United States: A SEER Retrospective Cohort Study".
    Role: Biostatistician / Epidemiology & Survival Analysis Consultant
    Domain: Oncology, Real-World Evidence (RWE), Population-Based Studies
    • Data Source: SEER (Surveillance, Epidemiology, and End Results – US National Cancer Institute)
    Tools: R, Survival Analysis, Cox Models, Kaplan–Meier, Epidemiological Methods.
    Led the biostatistical and epidemiological analysis of a large population-based retrospective cohort study using the SEER database, aiming to evaluate:
    • The incidence of colorectal cancer with peritoneal metastasis
    • Overall survival and survival determinants in affected patients
    • Prognostic factors influencing outcomes in a real-world US population
    This project provides real-world evidence to support clinical understanding and research in advanced colorectal cancer.
    Epidemiological & Statistical Analyses:
    • Construction and cleaning of a large retrospective cohort from SEER
    • Estimation of incidence rates and temporal trends of peritoneal metastasis
    • Descriptive epidemiology: Age, sex, tumor characteristics
    • Disease stage and metastatic patterns
    • Survival analyses: Kaplan–Meier survival curves Median survival,Long-term survival probabilities,Multivariable Cox proportional hazards modeling to identify: Independent prognostic factors, Risk-adjusted survival differences.
    Cancer Machine learning Oncology Statistics Epidemiology Survival Analysis
Check out Zaher's experience

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Education

  • PhD in Biostatistics
    Université de Paris
    2008
    Risque d'émergence d'un pathologie dans une population
  • Master in Biostatistics
    Université de Montpellier, INRA, ENSA
    2005
    Modèles et outils de la biostatistique

Certifications

Skill set

Python
R
Biostatistics
Oncology
Statistical modeling
Python (Programming Language)
Clinical trials
AI and Advanced Analytics
Git
Survival analysis
Clinical research
Performance Optimization
Data Cleaning and Preprocessing
Predictive Modeling
Time Series Analysis and Forecasting
Exploratory Data Analysis
Data Visualization

Categories