You will be part of our new Life Sciences Development business unit.

As a Data Scientist you are responsible for:

  • Analyzing, interpreting, and labeling large amounts of clinical data (structured and unstructured data, physician notes, radiology images) and presenting findings in a clear and consistent manner to your team members
  • Applying machine learning and deep learning on hospital data to develop prediction models for adverse events and other relevant use cases helping with treating the patients of our customers
  • Clinically evaluating the results of the prediction models
  • Understanding the functional requirements of our customers, taking part in developing new prediction applications end-to-end, and documenting your accomplishments
  • Developing solutions based upon best practices shared in the team, methodologies, and state of the art algorithms

What you bring to the table

  • You hold a master’s degree in biomedical engineering, (medical) computer science, bioinformatics, statistical data analysis, data science, or equivalent discipline
  • A medical background is an asset
  • You had a first experience in programming, ideally in developing natural language processing applications
  • You have conceptual knowledge of the software development lifecycle (e.g. unit testing, optimization, scalability, continuous integration, debugging, and documentation)
  • You are familiar with analyzing, processing and visualizing data, and with some of the following technologies or techniques:

SQL

Python

Angular

Natural language processing

HL7-FHIR

Linux

  • Experience with the following is a benefit:

Scrum

Jira

Java

Google Cloud

Microsoft Azure

  • You are a problem solver with an analytical mind
  • You are eager to learn and curious about the latest trends and developments in the healthcare industry
  • You have good communication skills and you can translate complex ideas, concepts, and reports into clear presentations
  • You are fluent in English and German, and knowledge of French is appreciated.