Data Scientist at Helsingin yliopiston
Helsinki, , Finland -
Full Time


Start Date

Immediate

Expiry Date

18 Nov, 25

Salary

0.0

Posted On

19 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Teamwork, Python, Databases, Biologists, Presentation Skills, Shell Scripting, Linux, English

Industry

Pharmaceuticals

Description

Join Us as a Data Scientist at FinnGen!
Location: Helsinki, Finland
Project: FinnGen at the Institute for Molecular Medicine Finland (FIMM)
Are you passionate about advanced data analytics and eager to make a meaningful impact in healthcare? Would you like to work in a multidisciplinary team of world-class experts to decipher large real-world health data? Join our team at FinnGen, one of the leading and largest health research projects globally, and be part of groundbreaking discoveries that can transform lives.

MUST-HAVE QUALIFICATIONS:

  • Doctoral or master’s degree in a relevant field
  • Strong statistical background with either R or Python, with the ability to work in both worlds.
  • Experience with databases (SQL)
  • We work with Linux in large secure computing environments. Fluency in Linux and knowledge of shell scripting is required.
  • Good communication and presentation skills in English
  • You enjoy teamwork with professionals of varied backgrounds (e.g. medical doctors, statisticians, biologists, lawyers)
  • Independent problem-solving attitude combined with meticulous mindset in an environment that requires understanding both the big picture and attention to detail.
Responsibilities

As a Data Scientist, you will play a critical role in:

  • Supporting research work: Your primary role would be to support clinically oriented teams that work with the rich and multimodal longitudinal data in specific disease areas (including e.g. Alzheimer’s disease, pulmonary diseases, inflammatory bowel disease)
  • Generating insights from decades of longitudinal health data: Real-world health data is extremely complex, rich, and multimodal. Before we can ask questions, we need to first understand how it behaves and how it is produced in complex health care processes.
  • Statistical modelling: Depending on your previous competence, building advanced statistical, causal, and predictive models describing disease progression and treatment processes. You will have the support of leading clinical and methodology experts in the field.
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