AWS, Azure, CSS, Data science techniques, Django, Employee life cycle, Google Cloud Platform (GCP), HTML, Java Programming, JavaScript, Linux Operating system, Machine learning techniques, Natural Language Processing (NLP), Node.js, Python Programming, PyTorch, React.js, Scikit-learn, TensorFlow, UI design, UX design
The Role
Pangaea is looking for full stack engineers who will closely collaborate with the technical team, clinical team and design team. We need our developers to implement the graphical design for our product so it effectively demonstrates the functions of our research technology in the context of the end user behaviour. You will develop the front-end and/or back-end to support demo presentations and will work closely with researchers.
Key technical responsibilities will include:
Requirements
Personal traits:
Technical Skills:
Nice To Have
Perks And Benefits
Application Contact Information
Please send your latest cv along with a cover letter and public links to your previous code, packages and/or demos to your full stack development (which do not include any confidential or proprietary information) to careers@pangaeadata.ai.
General Information
Pangaea Data’s headquarters is in London (UK) with teams in San Francisco (US) and Hong Kong. For more information, please visit www.pangaeadata.ai.
Pangaea Data is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, sex, sexual orientation, gender identity or expression, religion, national origin or ancestry, age, disability, marital status, pregnancy, protected veteran status, protected genetic information, political affiliation, or any other characteristics protected by local laws, regulations, or ordinances.
Pangaea Data, headquartered in London with additional offices in San Francisco and Hong Kong, is the driving force behind PIES, an AI-powered software product. PIES has demonstrated its remarkable ability to identify six times more suitable patients, including those who are undiagnosed and miscoded. Furthermore, it has enhanced screening success rates by an impressive 400%, while also streamlining the process by saving 90% in time. This efficienc