Job description

Do you want your work to have a real purpose? Use your data science, AI and machine learning skills to revolutionize health care and save millions of lives. Together, we can make a difference – Join our team 🙂!

About Us

DIGESTAID is dedicated to advancing digestive healthcare through cutting-edge Artificial Intelligence solutions. Our interdisciplinary team comprises gastroenterologists, researchers, and engineers, all driven to revolutionize diagnostics and treatments in gastroenterology. We aim to enhance the accuracy and effectiveness of diagnostic tools and therapeutic methods, of diagnostic tools and therapeutic methods, including anoscopy, cholangioscopy, capsule endoscopy and even going beyond and entering fields of gynecology, such as colposcopy.

Having recently secured seed funding, we are on the lookout for top talent passionate about AI for good. Join us and be part of a mission-driven team focused on making a significant impact in the field of gastrointestinal software.

About the role

As a Health Data Scientist / Machine Learning Engineer you will delve into interesting datasets, extract actionable insights, and refine AI models to create innovative health tools. You’ll collaborate closely with our CAIO (Chief Artificial Intelligence Officer) and a multidisciplinary R&D team, and your primary focus will be on creating, optimizing, and evaluating machine learning models tailored to improve diagnostic accuracy and therapeutic outcomes across various medical domains.

This is an excellent opportunity for a Data Scientist or ML Eng who is passionate about delivering practical AI solutions and enjoys taking on challenges that involve data science tools.

Key Responsibilities

Develop, optimize, and evaluate machine learning models to enhance the performance of our data science health tools.
Collaborate with the R&D team to translate clinical needs into AI solutions.
Conduct research and experiments to enhance the performance of AI solutions.
Implement and maintain software in a production environment.
Stay updated with the latest advancements in machine learning, time series analysis/processing, deep learning, and computer vision for health applications.

Requirements (must-have)

Bachelor’s or Master’s degree in Data Science, Computer Science, Biomedical Engineering, or equivalent.
Proficiency in Python, ML libraries (e.g., TensorFlow, Scikit-learn, PyTorch), and bash scripting.
Demonstrated experience in data science, machine learning, deep learning, time series processing, or computer vision (suggested: 2+ years).
Solid understanding of data structures and software engineering practices.
Good English communication skills.
Eagerness to learn everyday: We don’t expect you to know everything, we only expect you to be eager to learn and gain experience in the technologies and tools needed to develop our solutions.
Hands-on responsibility: You are expected to be proactive, seek solutions with the team and with the AI community, and take on projects, not tasks.

Desirable Qualifications (nice-to-have)

PhD with a focus on Machine Learning or Data Science.
Proven expertise in PyTorch, TensorFlow, GitHub Actions, and working with Google Cloud environments.
A track record of impactful data science or machine learning projects (preferred: 4+ years of experience).
Proficiency in software engineering best practices, including unit testing and logging.
Knowledge of MLOps practices.
Familiarity with Google Cloud environments and products.
Good track in data science or machine learning projects. Reference: +4 years experience
Familiarity with medical data and regulatory considerations is a plus.
Strong skills in data visualization and the ability to present complex data insights effectively.