reedelsevierhq Reed Elsevier
Purpose of the Job
The services that Elsevier provides are becoming increasingly dependent on Smart Content to support Elsevier’s corporate strategy of greater volume, types and sophistication of content. Elsevier is looking for an junior data scientist with a focus on Machine Learning and Statistical NLP techniques to help build state of the art applications for the health sciences domain. Hands on coding of NLP/ML algorithms an absolute must.
The junior data scientist will participate in the the design, prototyping and sometimes implementation of TDM/ML applications for our businesses. These applications have two main goals: cost savings by building workflow efficiencies or revenue generation by building front end features. You will work closely with both the nursing education and health sciences teams. Sample projects may include recommender systems for adaptive nursing content, extracting medical information from medical health care records, or search algorithms.
You will also work closely with the EMMeT (Elsevier Medical Merged Taxonomy) team providing data analytics on EMMeT and related terminologies to support decision-making, designing automated approaches to bulk updates, ontology validation and terminology mappings, and will bring NLP expertise to the team. You will work with a team of medical experts, as well as product leads to determine how to best build and leverage semantic capabilities. Knowledge of database query language (SQL) and scripting language (Python) are mandatory. Experience with Natural Language Processing application is necessary, and experience with medical terminologies such as UMLS, SNOMED CT, ICD-9, ICD-10, CPT, LOINC etc is a plus.
Main Activities and Responsibilties
Text and data mining
Bring active experience in to the organization on extraction text and data information from structured and unstructured data. Applying and developing these techniques, the junior data scientist will drive the implementation of automated indexing and annotation processes. Also well-versed in machine learning, he or she will bring new processes into the organization in order to improve (in cost and time-efficiency) the data excerption processes in Elsevier. This work includes the application of Elsevier's taxonomy and ontology assets to a wide variety of content – as well as drive developments in the application of and expansion on these vocabularies.
Data analytics to support businesses and products
Analyze extracted information to drive such processes as automated and manual data cleansing. Data analytics can also be used to identify research trends, or drive decision for our content acquisition strategy. Using visualizations tools to present the extracted data to be ready for consumption will be another key ability.
Contribute expertise on data extraction and NLP matters
Serve as an NLP/Machine Learning expert in the health sciences team. The Junior Data Scientist is also part of the the wider team Content and Innovation team. Contributing to a culture of product and process innovation, this person will be a trusted resource in new development projects in Elsevier. The person will connect IT developers and (content) subject matters experts, translating information needs into software development. As a specialist member of the team, the junior data scientist will serve as a specialist in his/her own field.
Proving and showcasing methodology
This person will prove the utility of new methods in a scientifically sound way. To show the value of new types of extraction and techniques, visualisation and presentation of the value of the extracted data will be another key ability.
Functional and Technical Competencies
Proven development experience in some relevant implementation platforms for NLP tasks – knowledge of Python, SQL, and R
Experience using *nix systems, open source software and libraries
Proven experience with text normalization and processing, writing NLP, Parsers, and Spell checkers
Familiarity with NLP applications to some healthcare problem is a requirement.
Familiarity with taxonomy applications across scientific and healthcare disciplines is a plus
Experience with internationalization, validation techniques, and using statistical techniques in decision making.
Able to work with a variety of stakeholders at the mid and senior management level
Ability to drive new developments and implement process changes and disruptive technologies in the organization.
Familiarity with agile software development.
Good communication and documentation skills with the ability to convey complex technical concepts to non-technical professionals.
Adopts pragmatic approach when choosing and implementing the right technologies to solve a problem, and develops with success metrics
Education, Knowledge, Skills and Experiences
University graduate (Master of PhD level) computer science, computational linguistics or an associated area.
Technical or Research experience working in Natural Language Processing (NLP) especially in entity extraction, word-sense disambiguation, information clustering and data mining requierd.
Experience with automated concept extraction and curation workflows in the health domain is highly valued; knowledge of validation techniques, and using statistical techniques in decision making also valued.
Candidates bringing industry experience to the job are preferred.
Elsevier is the world's leading provider of scientific, technical and medical (STM) information, tools and resources. A global company based in Amsterdam, Elsevier partners with scientists, researchers, healthcare providers, educators and decision-makers in academic institutions, governments and corporations to help them find, evaluate and use information. Our breadth of content is unparalleled, spanning virtually every STM field in the world and includes such distinguished brands as Gray's Anatomy, The Lancet and Cell. Using innovative technology, we deliver our content through tools that help our customers be more productive and successful in their work. ScienceDirect delivers the worlds' leading journals electronically to over 11 million readers in 200 countries. And physicians in 95 percent of teaching hospitals rely on ClinicalKey to get critical information that can save lives. Elsevier employs over 7,000 people in more than 70 offices worldwide. We are an employer of choice, attracting and developing talented and creative people who thrive in a challenging and fast-paced environment. We offer an excellent compensation and benefits package as well as a real opportunity for career growth in a growing organization. Elsevier is an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. If a qualified individual with a disability or disabled veteran needs a reasonable accommodation to use or access our online system, that individual should please contact 1.877.734.1938 or firstname.lastname@example.org.
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