Job Description
Role Description:
Are you looking for a new career opportunity that will allow you to develop and use cutting-edge AI technologies to solve challenging NLP problems while making a positive impact on the world? If so, we would love to hear from you! Dyania Health is looking for NLP Applied Scientists to help us transform the way in which machines process biomedical information, and revolutionize the way in which clinical trials are conducted. You will be working alongside team members with deep technical expertise in NLP, top medical professionals (MDs, pharmacology PhDs, and others), and an experienced product team. The ideal candidate will have strong foundations in computer science and ML/NLP, superb communication skills, and a proven track record of delivery under tight deadlines.
Requirements
Required Qualifications:
Preferred Qualifications:
Responsibilities:
Team Culture:
• We lead with empathy for patients and our teammates.
• We value small egos, self-awareness, and humility in our teammates.
• We appreciate flexible and adaptive attitudes towards solving problems, as strategic priorities may shift.
• We love diversity of thought, perspective, working style, skill set, knowledge, and interests amongst our team.
• We value open dialogue and brainstorming across multidisciplinary teams.
Dyania Health is an equal opportunity employer that is committed to workplace diversity and inclusion. We do not discriminate on the basis of race, gender, gender identity, color, religion, national origin, sexual orientation, or any other legally protected characteristic as outlined by federal, state, or local laws.
Dyania’s mission is to deploy their medically specialized and proprietary Synapsis AI to automate manual chart review, one of the most inefficient and time-consuming processes in modern healthcare, thereby empowering clinicians to deliver optimal care, precisely when patients need it. Dyania’s system is being used at large healthcare systems to unlock enterprise-wide clinical trial pre-screening, run automated chart review for observational studies, and automate complex registry reporting, dramatically reducing manual workloads and ensuring more accurate and timely patient care.