Data Scientist
Reference number: 2025-0081
- Heidelberg
- Full-time
- Policy and Implementation Research
“Research for a life without cancer" is our mission at the German Cancer Research Center. We investigate how cancer develops, identify cancer risk factors and look for new cancer prevention strategies. We develop new methods with which tumors can be diagnosed more precisely and cancer patients can be treated more successfully. Every contribution counts – whether in research, administration or infrastructure. This is what makes our daily work so meaningful and exciting.
For our Division Policy and Implementation Research the German Cancer Research Center is looking for as soon as possible a
The DKFZ Hector Cancer Institute at the University Medicine Mannheim (UMM) was established in 2019 in the frame of a partnership between the German Cancer Research Center (DKFZ) in Heidelberg, the University Medical Center Mannheim, and the Medical Faculty Mannheim of Heidelberg University with generous support from the Hector Foundation II (https://hector.dkfz.de/index.html). The aim is to carry out excellent translational cancer research in the fields of precision oncology, cancer prevention, early detection, and survivorship.
Our newly established Division for Policy and Implementation Research within the DKFZ Hector Cancer Institute is dedicated to bridging the gap between evidence and policy/practice. Through pioneering research, and transdisciplinary collaborations, we strive to propel advancements in the field of cancer prevention, ultimately contributing to public health.
Your Tasks
We are looking for an outstanding, and highly-motivated data scientist to join our division. The successful candidate will use advance data science methods to contribute to innovations in the areas of policy and implementation research for cancer prevention. Responsibilities also include publishing findings in high-impact journals, writing grant applications, and participating in innovative knowledge translation methods to disseminate findings to key stakeholders. This role offers an exciting opportunity to work with cancer prevention research experts, policymakers and the community.
Your Profile
Applicant must hold a PhD in data science, biostatistics, computer science, or a related field. Proven experience in applying data science techniques to health research, and proficiency with statistical analysis and programming are required. The ideal candidate should also have a strong interest in policy and implementation research and passion for bridging the gap between evidence and policy/practice. Excellent communication and organization skills and proficiency in English are mandatory.
We highly value independent analytical thinking, sense of responsibility and, most importantly a collaborative team spirit. Applicant should enjoy working in an international and interdisciplinary environment.
We Offer
Excellent framework conditions: state-of-the-art equipment and opportunities for international networking at the highest level
30 days of vacation per year
Flexible working hours
Remuneration according to TV-L incl. occupational pension plan and capital-forming payments
Possibility of mobile work and part-time work
Family-friendly working environment
Sustainable travel to work: subsidized Germany job ticket
Unleash your full potential: targeted offers for your personal development to further develop your talents
Our Corporate Health Management Program offers a holistic approach to your well-being
Are you interested?
Then become part of the DKFZ and join us in contributing to a life without cancer!
Prof. Dr. Connie Hoe
Phone: +49 (0)160 94460635
Applications by e-mail cannot be accepted.
We are convinced that an innovative research and working environment thrives on the diversity of its employees. Therefore, we welcome applications from talented people, regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical ability, religion and age. People with severe disabilities are given preference if they have the same aptitude.
