Data Scientist - Munich, Deutschland - deepeye Medical GmbH
Beschreibung
What we are doing
Our mission is to prevent vision loss and ultimately blindness by developing AI software that assists eye doctors in therapy planning for their patients.
We use computer vision deep learning models(AI) trained on thousands of cases and millions of images to identify and predict disease progression.
The decision support algorithm targets popular eye diseases like Age-related Macular Degeneration (AMD, 7.5mio affected in Germany alone).Tasks
Your responsibilities as Data Scientist
- You are responsible for building and optimizing data pipelines to bring together information from different source systems, i.e. imaging, text and clinical data
- You bring curiosity, problemsolving instinct and statistical and mathematical knowledge.
Requirements:
What we are looking for
Your must-haves
- 3+ applied knowledge of deep learning and machine learning (ML), including a working knowledge of CNN, RNN, UNet and ML techniques (crossvalidation, train/validation/test set, regularization)
- 5+ years of applied experience in computer vision and imaging analysis (2D/3D image processing, segmentation, image normalization, ideally medical imaging)
- 5+ years of applied programming experience with Python and common ML frameworks e.g. Tensorflow, Py-Torch, etc.
- Evidence of data driven product development and delivery
- Degree in data science/engineering, bioengineering, computer science, medical physics or similar
- Experience to work in interdisciplinary teams of doctors, data scientists, data and software engineers
- Experience in analyzing, evaluating, and integrating data using relational databases (e.g. PostgreSQL)
- Workinglevel English (C1 or higher)
Benefits:
What we offer
- Direct impact on improving quality of life for patients & doctors
- Immediate responsibility for reporting, projects & fast personal growth
- Flexible working hours, remote work & office at Munich main station
- Competitive compensation, startup culture & an international rock star team
Reach out to us with information about your availability, salary expectations and a link to your conclusive profile (GitHub, LinkedIn, CV).
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