What are the responsibilities and job description for the NLP Engineer position at EApps Tech LLC dba Magicforce?
Job Title: NLP Engineer
Location: Remote
Duration: 1 Year
Job Description:
•Ability to read and comprehend both research papers and medical documents quickly and accurately, identifying the meaning of specific text and phrases, and apply the methods and results to real world client problems
•Familiarity with clinical guidelines (e.g. NCCN in oncology, GOLD for CPT) and their application and uses.
•Familiarity with biomedical life sciences include the knowledge bases involved in pre clincial or translational research (i.e., GenBank, PDB, KEGG, PubMed, etc.)
•Able to develop NLP and AI protocols for guiding the application of NLP and AI across the entire NLP/AI development lifecycle to solve real world problems.
•Oversees the development of the underlying information model(s), the annotation guidelines, annotation tasks and related processes/guidelines
•Review and manage the work from the annotation team including working with annotators, refining annotation processes, and defining new annotation tasks
•Working with the NLP scientists, defines NLP/AI methods to be used for training, model validation and performance assessment, and production
•Preferably a PhD/MD/DO with prior life sciences experience in a research or clinical research setting.
Experience: -
•Minimum 3 years of professional work experience as a quantitative analyst or applied analytics technical leader (healthcare experience preferred)
•Mastery of statistical software, scripting languages, and packages- preferred R, Python, SQL
•SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of other databases/date-sources.
•Solid understanding of supervised and unsupervised ML techniques.
•Solid understanding of data structures, software design and architecture.
•Ability to work independently and take initiative, but also a co-operative team player.
•Proficient at interpreting business questions and applying concepts to data.
•Excellent Communication and presentation skills, proficiency in data interpretation
Educational Qualifications: -
•Master's degree in computer science, Statistics, Engineering, Physics, or other highly quantitative and technically oriented field