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Mohamed HenniMH

Mohamed Henni

Senior Statistician

€660/day
Bruxelles, BE
8-15 years

Average response time: 1 hour

About Mohamed

Senior statisticien with more than 10 years of experience working in pharmaceutical and vaccine industries. I worked in preclinical, clinical, assay development, non-clinical teams, as a solo statistician and within statistical departments and groups. I can do the functions of principal statistician as well as a statistical programmer.
  • English

    Fluent

  • French

    Native or bilingual

Remote only
Primarily works remotely

Experience

  • Glaxosmithkline UK
    Senior statistician
    PHARMACEUTICALS INDUSTRY
    January 2020 - Today (6 years and 5 months)
    Rixensart, Belgium
    Freelance Subcontractor for Alsinova.

    Member of the VxR&D GVGH GSK Italy team.

    I am a statistician who turns data into clear, actionable insights. I collect, clean, and analyze data to identify patterns, test hypotheses, and support decision-making. Using statistical models and tools, I translate complex numbers into meaningful conclusions for businesses, research, or policy. I design experiments, assess risks, and ensure data accuracy and reliability. My work helps solve problems, optimize performance, and guide strategy by providing evidence-based answers. Whether working with large datasets or focused studies, I make information understandable and useful, helping others make informed decisions with confidence.
    Shiny RStudio SAS
  • GSK
    Statistician
    PHARMACEUTICALS INDUSTRY
    October 2017 - November 2020 (3 years and 1 month)
    Wavre, Belgium
    - Variance analyses and statistical tests
    - Features selection
    - Features engineering and augmentation
    - Models selection and parameters optimization
    - Ensemble predictions and sequential boosting algorithms
    - Data visualization using various libraries (ggplot, plotly, ..)
    - Development and deployment of Shiny applications (user interface and server logic) within company servers
    - Redaction of reports and analyses using R Markdown and R Notebook
    - Use of pre-trained classification and regression models with Keras and fine-tuning them for deployment
    - Use of Reinforcement learning algorithms (Q-learning)
    R Statistics SAS Shiny
  • UCB
    Non-clinical Statistician
    PHARMACEUTICALS INDUSTRY
    November 2016 - September 2017 (10 months)
    Braine-l'Alleud, Belgium
    Build predictive models for bioassays using new statistical methodology to compare ELISA dose response curves.
    Machine learning R ELISA Statistics

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Education

  • Master's degree with high distinction
    University of Brussels
    2017
    Master's degree in applied statistics and machine learning algorithms.
  • Bachelor's degree
    University of Algiers
    2015
    Bachelor's degree in applied mathematics and computer science.

Skill set

Categories