NLP Applied Scientist

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 NLPApplied 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:

• Graduate degree in a relevant field (Computer Science, Mathematics, Electrical Engineering)
• 2+ years experience in building and deploying ML models
• Experience in applying transformer-based deep-learning techniques to challenging NLP problems
• Fluency in Python and experience with Python-based ML frameworks such as PyTorch
• Outstanding communication skills

Preferred Qualifications:

• Publications in top-tier NLP conferences
• Background in classical computational linguistics
• Experience with Java (or Kotlin/Scala) and/or a functional programming language

Responsibilities:

• Design, build, evaluate, and deploy algorithms and models for accurately extracting medical information from structured and unstructured data sources
• Work closely with product, UX, and clinical teams to prototype and test new functionality
• Analyze performance results and convey your analyses to relevant stakeholders
• Conduct research, publish and present your findings at relevant scientific venues

Team Culture:

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.