Senior Scientific programmer/data analytics engineer

The University Medical Center Utrecht's Department of Data Science and Biostatistics Real World Evidence group is looking for a senior-level professional with data science and software engineering skills to participate in the development, maintenance and optimization of real-world health data transformation & analysis pipelines. These pipelines are used to process large amounts of digital healthcare data from routine patient care into real-world evidence, allowing, amongst others, studies on the safety and effectiveness of vaccines and medicines.

You will work in a dynamic and esteemed team of programmers, statisticians and data scientist, and participate in high impact research on medicines effects and safety for a variety of stakeholders.

The successful candidate is a skilled and enthusiastic programmer with an MSc or PhD degree in Informatics, Data Science, Econometrics or a related field and have:

• A broad interest in medical research
• Excellent knowledge of SQL and different database management systems such as DuckDB, SQLite, MySQL, etc.
• Excellent knowledge of both R and Python scripting
• Strong understanding of data integration and ETL tooling (not just using scripting)
• Experience transforming real-world data for research purposes
• Background in both academics and IT
• Have a strong vision on tooling and data quality
• Proficient in Git and GitHub
• Experience with continuous integration with GitHub Actions

Moreover, fluency in English, both verbal and in writing, is required. Being fluent in Dutch is an advantage.

The maximum salary for this position (32 - 36 hours) is € 5.504,00 gross per month based on full-time employment.

In addition, we offer an annual benefit of 8.3%, holiday allowance, travel expenses and career opportunities. The terms of employment are in accordance with the Cao University Medical Centers (UMC).

The Julius Center for Health Sciences and Primary Care is one of the 10 divisions within the UMC Utrecht. The Julius Center aims for a leading role in the acquisition and dissemination of knowledge in the field of Health Sciences and Primary Care. Through the years, the Julius Center has distinguished itself through high quality scientific research and education. The department of Data science & Biostatistics focuses its research and main projects on Data Science, Clinical trials methodology, Real World Evidence and Methodology for high dimensional (big) data. The Real-World Evidence team has an academic staff of about 30 statisticians, epidemiologists and data scientists and PhD students. The Real-World-Evidence group in the department of Datascience & Biostatistics focuses on transformation of distributed big routine health data into evidence that can be used by medicines regulators (e.g. European Medicines Agency) and health care professionals as part of a learning health ecosystem.