Fabric

Data Scientist (Remote)

Job description

About Fabric

Fabric is a health tech company that powers healthcare providers to move faster, work smarter, and deliver better care through its care enablement system. The system offers three solutions: In-Person Care Suite, Virtual Care Suite, and Engagement Suite. Leveraging conversational AI and intelligent adaptive interviews, Fabric unifies virtual and in-person care across intake, triage, routing, and treatment while automating workflows for staff. Built by a team of physicians and clinical informaticists, Fabric protocols uphold excellence in care quality while offering omnichannel access for patients. The results enable clinicians to work 2-10 times faster (dependent on setting), decrease call center volume by 15%, and increase utilization of unfilled visit blocks. Some of Fabric’s customers include Luminis Health, OSF HealthCare, MUSC Health, and Intermountain. Fabric is backed by Thrive Capital, GV (Google Ventures), Salesforce Ventures,Vast Ventures, BoxGroup, and Atento Capital.


About the role

We are seeking a talented Data Scientist to join our growing team. You will play a pivotal role in developing and implementing cutting-edge AI solutions that revolutionize patient communication within the healthcare landscape.


What you'll do

  • Design, develop, and deploy machine learning models for various tasks, including:
  • AI-powered diagnosis engine: Analyze patient data to assist healthcare professionals with accurate diagnoses.
  • Natural Language Processing (NLP): Build sophisticated systems that understand patient intent from their inquiries, leading to improved communication and self-service options.
  • Generative AI: Utilize Large Language Models (LLMs) to generate informative and personalized patient-facing content.
  • Collaborate with engineers, researchers, and product managers to define project scope, gather requirements, and ensure successful integration of AI solutions.
  • Participate in data exploration, cleaning, feature engineering, and model evaluation.
  • Stay up-to-date on the latest advancements in machine learning, NLP, and LLMs relevant to healthcare applications.
  • Prepare clear and concise documentation for technical and non-technical audiences


Qualifications

  • Master's degree in Computer Science, Statistics, Machine Learning, or a related field (PhD preferred).
  • Proven experience in applying machine learning techniques to real-world problems.
  • Hands-on with model evaluation
  • In-depth knowledge of NLP concepts and techniques, including text preprocessing, sentiment analysis, and intent recognition.
  • Familiarity with LLM architectures and experience in fine-tuning or developing LLM-based applications (a plus).
  • Strong programming skills in Python, with proficiency in libraries like TensorFlow, PyTorch, Scikit-learn, and spaCy.
  • Excellent communication, collaboration, and problem-solving skills.


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