Senior Data Analyst

Sr. Data Analyst


We are currently looking for a Senior Data Analyst that will lead data harmonization projects. Work with clients to understand and map their data to a common data model to facilitate research and knowledge extraction. Develop population effect level estimation, patient level predictive models and other impactful machine learning and analysis solutions.


Manage a data harmonization project from start to finish

Analyze data models for observational patient data in use by hospitals, clinics, universities and other clients

Work with the client to define the mapping and approach needed to transform the client’s data to the OMOP CDM (Common Data Model)

Work with the client to evaluate data quality and define inclusion/exclusion criteria

When needed, codify local data categorizations and map to standard terminology

Define and plan the implementation and execution of the ETL, and work with team members to implement and deploy the solution

Effectively document and communicate technical data analyses, architecture, mapping designs, quality controls, and results

Required Qualifications

  • Degree

    Advanced technical degree (Master) in Computer Science, Bioengineering, Data Science, Physics, Applied Sciences
    or similar field

  • Experience

    - 3+ years of experience as analyst or similar role
    - Experience analyzing and extracting meaningful insights from data
    - Experience with advanced visualizations and visual analytics
    - Data modelling experience using relational database
    - Experience working in health or life science domain

  • Programming Skills

    Good programming skills in Python, R, or other languages

  • Interests

    Strong interest in health-data related cutting-edge technologies and methodologies

  • Language

    Fluent in English, knowledge of Dutch, French and other languages a plus

Preferred Qualifications

  • Experience

    - Experience designing and implementing ETL solutions
    - Experience with healthcare IT and systems (EHR/EMR, health registries)
    - Experience with Machine Learning methods for creating prediction models based on observational data
    - Experience with OMOP CDM and OHDSI tools and libraries

  • Knowledge

    - Knowledge of statistical tools for analyzing observational data
    - Knowledge of medical terminologies and controlled vocabularies (ICD-10, SNOMED, LOINC, RxNorm, etc.) used in healthcare data
    - Knowledge of statistical tools for analysing observational data
    - Familiarity with Python data science libraries (pandas, numpy, scipy, sklearn, etc)