Overview

Orbit is a multi-awarded, purpose-driven startup based in Munich (Germany) with the commitment to empowering people living with chronic conditions to take better control of their health and lead a quality life. We do this by harnessing the power of IoT, sensor, and AI technologies to ensure people get access to the intervention and personalize care they need, even when they are away from their doctors.

Our first solution, Neptune, enables physicians to effectively personalize treatments for patients with Parkinson’s, helping them attain optimal symptom control. Orbit is also developing a digital biomarker platform that enables the integration and orchestration of an array of digital health solutions and devices to address co-morbidities and multiple chronic diseases.

We are looking for a highly skilled individual with an extensive Data Science expertise (AI and ML background) to be our Lead Data Scientist. If you are passionate about building pioneering MedTech products to solve real-world problems, developing talents, and making a difference in patients’ lives, we want to meet you!

Your Role & Responsibilities

Research, Development, and Evaluation of state-of-the-art deep learning and machine learning algorithms
Development and implementation of Data Science and AI/ML workflows geared towards extracting actionable information from time series data
Setup of continuous learning environments for optimization of AI-based models concerning robustness and stability
Work closely with product and clinician teams to plan projects and structure work in an Agile development process
Document ML-based systems and facilitate architectural reviews of projects
Identify areas of innovation, formulate research hypotheses, and rapidly prototype new models

Company:

Orbit Health

Qualifications:

Technical Skills & Qualifications

M.Sc. or PhD in Data Science, Computer Science, Computational Statistics, Mathematics, Informatics, Physics etc.
Preferably a senior-level understanding of classical and deep learning-based ML methods (e.g., CNNs, DL Auto-encoders, etc.)
Knowledge and experience of relevant analytics, visualization and ML libraries is vital (e.g., SciPy/NumPy, Pandas/Matplotlib, Keras/TensorFlow, PyTorch, etc.)
Experience with Model Deployment / ML Ops is preferred
Experience with tooling such as AWS SageMaker, AML, Cognitive Services and related cloud-based services (e.g., Model-as-a-Service) is desirable
Experience with Time-Series Data is a bonus
Communicating effectively in an interdisciplinary environment (AI/ML, product management, regulatory, clinical)
Background

Have practical experience with ML in research and development projects
Significant experience as a Data Scientist
Experience in building data solutions incrementally, integrating and managing datasets from multiple sources.
Have solid programming experience in Python, R or Julia, however significant experience in other high-level languages is beneficial for deployment / production environments (e.g., C/C++/C#/Java/Rust)
Experience in both rapid prototyping and experimentation, as well as in bringing machine learning models into a stable and cost-effective production environment
Business proficient in English (spoken and written)

Educational level:

Master Degree

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