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Data Science Lead (CV + ML)
Summary by AIEngineer.careers
Data Science Lead (CV + ML) is a Computer Vision Engineer role (full-time). with Neko Health. in BERLIN, DE. Imported listing (source: workmundi.com). Apply on the employer's site (workmundi.com).
Imported listing (source: workmundi.com) · Apply on workmundi.com
BERLIN · DE
—
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from workmundi.com
Neko Health is seeking a Data Science Lead (CV + ML) to develop and deploy computer vision and machine learning algorithms for clinical decision support. You will work on imaging problems such as skin and tissue imaging, collaborating with cross-functional teams to bring algorithms into production. The role involves owning problems end-to-end, from data to deployed models, and mentoring colleagues.
Responsibilities
- Develop, verify, validate and deploy computer vision and ML algorithms for clinical decision support.
- Own problems end to end, from vague questions and messy data to production models.
- Collaborate with hardware engineers, software engineers, medical doctors, and clinical researchers.
- Combine classical, geometric, and learned methods, using semi-, self- or weakly-supervised approaches.
- Analyze clinical study data and support regulatory readiness.
- Deliver production-quality code and integrate into backend infrastructure.
- Mentor colleagues and contribute to a culture of continuous improvement.
Requirements
- Extensive experience in modern computer vision and deep learning on real-world camera or sensor data.
- Track record of shipping algorithms to production under messy real-world conditions.
NH
Neko Health
Stockholm · SE · 1000+ employees
Neko Health is a preventive healthcare company founded in 2018 by Hjalmar Nilsonne and Daniel Ek. It combines proprietary hardware, software, clinical care, and research to provide an integrated health assessment designed to identify health risks proactively.
