Data Scientist
About the role
As a Data Scientist at Waiv, you will have the opportunity to improve medical research using state-of-the-art machine learning algorithms.
In this role, you will be involved in projects with international medical institutes or academic partners, pharmaceutical companies, as well as in our internal R&D projects.
What you will be doing:
- As an expert or a leader on our external projects you will:
- Collaborate with other members of Waiv’s team with varied backgrounds (ML engineers, project and product managers, medical affairs, pathologists) to deliver these projects.
- Discuss with doctors or clients to frame projects (what is the medical question? which data could we use to answer it?) and monitor them.
- Analyse medical datasets using machine / deep learning algorithms, as well as more traditional statistical methods.
- Write scientific papers and project reports.
- Participate in our internal R&D, improving Waiv’s methodology, including but not limited to regular literature review.
- As a scientific lead for the external projects you own, you will:
- Be responsible for the delivery of one or multiple engagements in parallel.
- Manage the project scope, team, planning and deliverables.
- Attend and/or present your work at medical or technical congress.
- Ensure client satisfaction, build and sustain relationships with senior executives.
Who we are looking for:
The successful candidate will have a ‘team-first’ kind of attitude; be independent, curious and detail-attentive; thrive in a dynamic, fast-paced environment; and be fun to work with.
Be passionate about the intersections of healthcare and AI.
Graduate (MSc) or PhD/Post-Doc in Computer Science-related field (machine learning, applied mathematics, computer science, software engineering) or have gained previous experience as a data scientist.
Knowledge and experience with machine learning and computer vision: you have already achieved projects with real-world data and are familiar with Scikit-Learn, convolutional neural networks, vision transformers, cross validation and statistical tests.
Experience with deep learning frameworks such as Tensorflow, PyTorch, etc.
Experienced with Python.
Excellent written and oral communication skills.
Highly organised and meticulous about details; capable of tackling complex problems logically and effectively; fun to work with; honest; excited to work hard in a dynamic, fast-paced environment.
Ways to stand out:
- Previous experience working with medical data, and in particular medical images (histology, CT, MRI, OCT, …).
- Adhesion to current best coding practices, methods, and standards (e.g. following PEP news, etc).
- Some prior knowledge of cell biology and/or cancer biology.
- Previous experience of teamwork on projects and/or implementing solutions for business.
- Authored journal publications on machine learning / deep learning applied for answering biological / disease questions.