Korro AI is pioneering a new approach to children’s healthcare. Our mission is to make comprehensive health, behavioral care, and well-being services accessible to every child. We leverage AI and computer vision to deliver in-depth analysis and enable integrated, personalized therapy. By extending care beyond the clinic, our platform empowers providers to monitor progress and support children in their everyday environments.
Korro’s Technology and Innovation AI group translates applied research into cutting‑edge products. Working at the intersection of Computer Vision and Artificial Intelligence, we transform ideas into real‑world solutions that directly impact pediatric care.
AI Data Science Engineer will drive Korro’s data and analytics infrastructure, including the data warehouse, BI systems, and AI‑enabled workflows . The objective is to build robust, scalable pipelines that enable a strong focus on advanced analytics and statistical modeling.
A core responsibility is the rigorous analysis of clinical and real‑world therapy data . The candidate will apply sound mathematical and statistical methodologies to evaluate studies, identify meaningful patterns in therapy progression, and generate insights that inform product and clinical decision‑making. Strong expertise in statistical modeling, hypothesis testing, and study evaluation is essential.
Working within the Technology and Innovation AI, the role requires close collaboration with engineers, AI researchers, medical experts, and product teams. While the focus is on applied analytics rather than deep learning or LLM training, the ideal candidate is AI‑ready : stays current with advances in AI, actively integrates modern AI tools (e.g., coding agents and AI‑assisted workflows) into the daily work , and continuously improves how analytics is conducted.
The ideal candidate combines analytical rigor, hands‑on execution, a product mindset, and a strong commitment to ethical AI in a pediatric healthcare context.
Veröffentlichungsdatum:
09 Mär 2026Standort:
DarmstadtTyp:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Erfahrung:
2+ yearsArbeitsverhältnis:
Angestellt
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