Clinical Data Annotator

Company

At Nym, we’re passionate about simplifying healthcare by automating the accurate interpretation of clinical language.

Our interdisciplinary team has developed innovative technology that can understand clinical language and provides an entirely new way of analyzing and decoding medical records into clear, concise, and actionable information. This ultimately ensures clinical and administrative teams can spend more time focused on patient care.

At Nym, the future is bright. Our engine currently processes over six million charts annually in more than 300 emergency department and urgent care settings across the US. We are backed by top-tier VCs and growing rapidly, with offices in NYC and Tel Aviv.

Come join us!

Role and Responsibilities:

Nym is seeking a part-time Clinical Data Annotator to join our growing Data team, reporting to Tal Serlin the Data Team Lead. This position involves 60 hours per month in a hybrid work environment and is located in our Tel Aviv office. You will be responsible for reviewing and labeling medical data, such as medical texts and patient records, for use in machine learning models and core company analyses.

As a Clinical Data Annotator, you will:

Annotate Clinical Data: Accurately label data with descriptions or medical codes and annotate clinical data sets to support machine learning and natural language processing (NLP) applications
Ensure Quality: Conduct quality checks to ensure consistency and adherence to the highest clinical standards
Collaborate: Work with cross-functional teams, including software engineers, linguists, NLP researchers, medical coders, and healthcare providers

Requirements:

MD or equivalent degree, certified Physician Associate (PA), or final-year medical student or above; must possess a solid understanding of medical terminology, anatomy, diseases, and treatments
Fluent in English, both written and spoken, with thorough expertise in medical terminology
Familiarity with coding standards such as ICD and CPT is preferred
Ability to conduct analytical work and proficiency in using Excel/Sheets or annotation tools; knowledge of SQL or Pandas is an advantage
Experience and familiarity with the United States healthcare system is preferred