Scientific Collaborator, Data Science and AI (Forensic Biometrics) | Data Scientist (m/w/d)
Bundeskriminalamt
Job Summary
This role seeks a Scientific Collaborator specializing in Data Science and Artificial Intelligence to join the Forensic Institute of the Federal Criminal Police Office (BKA) in Wiesbaden, focusing primarily on DNA analysis and forensic biometrics. The core responsibilities involve the end-to-end planning, development, coordination, and monitoring of cutting-edge AI solutions aimed at supporting criminal investigations and generating forensic reports. You will analyze current workflows to identify automation potential, implement pilot projects, and manage critical interfaces between IT, specialist departments, and management, ensuring the clear communication of AI benefits. Ideal candidates hold a Master's degree in Applied Computer Science, AI, or a related field, coupled with a minimum of two years of professional experience in developing AI methodologies, machine learning, and practical implementation of data-driven projects. This position offers a unique opportunity to apply advanced scientific methods directly to crime fighting and prevention efforts on both national and international levels.
Required Skills
Education
Completed scientific university degree (Master, Magister, or Diplom) in Applied Computer Science, Artificial Intelligence, Data Science, or a comparable technology and data-oriented degree with a focus on AI or machine learning
Experience
- Minimum 2 years in the development and application of AI methodologies, machine learning, and data analysis
- Minimum 2 years practical experience in the conception and/or implementation of AI projects or data-driven applications
Languages
Additional
- Willingness to travel nationally and internationally (approx. 3-5 times per year, typically up to one week); Basic understanding of legal requirements (especially EU AI Act), data protection, risk assessment, and ethical implications of AI; Willingness to work flexible hours; Readiness for continuous learning and interdisciplinary cooperation
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