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Alexandre AudibertAA

Alexandre Audibert

R/SAS Data Analyst

€420/day
Bruxelles, BE
8-15 years

Average response time: 1 hour

About Alexandre

I’m a Senior Data Analyst with 10+ years of experience turning complex datasets into clear, actionable insights. I hold a Master’s degree in Statistics (UCLouvain, Belgium) and have worked on large-scale projects for organisations handling sensitive and high-volume data (including healthcare and public programs).

I can help you with:

- Data cleaning, preparation and documentation (R, SAS, SQL)
- Descriptive and advanced analyses (regression, multilevel models, survival analysis, dashboards, KPIs)
- Reproducible reports and automated workflows (R Markdown / Shiny apps)
- Quality checks, data validation and methodology support for studies or programs
- Migrating existing SAS workflows to modern R-based solutions

My style is rigorous, clear and collaborative: I make sure methods are sound, results are easy to understand, and deadlines are respected. I work comfortably in English and French.

If you need reliable analysis and clean code rather than just “pretty charts”, I’d be happy to discuss your project.
  • French

    Native or bilingual

  • English

    Fluent

  • Dutch

    Basic

Remote only
Primarily works remotely

Experience

  • Université catholique de Louvain (UCLouvain)
    Data Analyst / Project Manager
    October 2013 - December 2021 (8 years and 2 months)
    Managed a regional hospital benchmarking project, analysing administrative and clinical data from multiple hospitals.
    Performed data cleaning, validation and advanced statistical analyses using SAS and R.
    Built indicators and dashboards to compare hospital performance and support decision-making for health authorities.
    Coordinated with stakeholders (hospitals, IT teams) and produced clear reports and presentations.
    ETL/ELT QlickView
  • Belgian Cancer Registry
    Data Analyst / Project Manager
    January 2022 - Today (4 years and 5 months)
    Data Analyst working with national cancer registry data.
    Design and maintain ETL pipelines in R and SAS to convert raw medical data into clean, reliable and well-documented datasets ready for analysis.
    Develop user-friendly Shiny tools and dashboards so non-technical users can explore indicators, monitor data quality and download tailored reports.
    Led the migration of core reporting and analysis workflows from SAS to R, including planning, code refactoring, validation of results and documentation.
    Build reproducible analysis workflows (R Markdown, Git) and collaborate with internal teams and external partners to ensure methods are transparent and results are easy to understand.

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