NLP Scientist

Role Overview: Miimansa is looking for a NLP scientist to join their team and be responsible for developing and prototyping novel methods for natural language understanding tasks for clinical texts. As a core contributor, you will work closely with academic NLP research groups, participate in NLU challenge tasks, and provide recommendations for the product roadmap and strategy. Key Responsibilities: - Develop and prototype novel methods for natural language understanding tasks for clinical texts - Collaborate with academic NLP research groups and participate in NLU challenge tasks and publications - Stay updated with advancements in SOTA methods relevant to the product pipeline - Provide recommendations for product roadmap and strategy based on research findings Qualifications Required: - Bachelor's degree or higher in computer science or engineering with a focus on language processing. Exceptional candidates with a bachelor's degree in CS and relevant experience will also be considered - At least 2+ years of experience in NLP and relevant projects. Requirements may be relaxed for candidates with a PhD - Sound understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering - Understanding of NLP techniques for language modeling, text representation, and semantic extraction techniques - Good grasp of current DNN architectures, training and evaluation methods in NLP, and ability to adapt them for clinical/medical data and problems - Proficiency in programming in Python and libraries such as Huggingface, Spacy, OpenAI API - Familiarity with NLP literature, thrust areas, conference venues, and code repositories - Willingness and ability to mentor engineering interns Miimansa is developing technology to accelerate the development of medical interventions and patient care. The company brings together expertise in clinical data management workflows, life sciences research, and AI to address major bottlenecks in experimental medicine, enabling easier execution and lower risk in clinical trials. The company encourages hybrid working arrangements and fosters a culture of collaborative learning and discovery, providing numerous opportunities for growth.,