RELX Hiring for Data Scientist – 1021-BA-305 at Chennai, Tamil Nadu Full Time

Data Scientist

Purpose of the Job

The services that Elsevier provides are becoming increasingly dependent on data science and analytics to support Elsevier’s corporate strategy of greater volume, data types, and sophistication of content to support our products and platforms in health markets. The Data Science Health Content Operations team is looking for a Data Scientist with a focus on Machine Learning, NLP, and Statistical techniques to help build state of the art applications for the health sciences domain.

This person will have hands on experience developing best models and standards as well as extensive knowledge of how to apply the right algorithms to the right problems. Our solutions depend heavily on concept indexing or annotation (using ontologies in the medical domain), relationship tagging and extraction (from clinical content and scientific literature) or automated generation of clinical topics. The ideal candidate will have academic or industry experience solving data science problems (topic modelling, entity extraction, named-entity recognition, concept tagging, word-sense disambiguation, information retrieval, clustering, supervised and unsupervised learning) using NLP, machine learning, deep learning, and statistical methods on vast quantities of data.

You will also work closely with the EMMeT (Elsevier Merged Medical Taxonomy) team providing data analytics support to EMMeT and Elsevier’s healthcare knowledge graph (H-graph) to support decision-making, designing automated approaches for ontology and graph development, ontology validation and terminology mappings. You will work with a team of medical and subject matter experts, as well as product leads to determine how to best build and leverage semantic capabilities.

Main Activities and Responsibilities

Text and data mining

Information extraction from structured and unstructured data. Also well-versed in machine learning, you will bring new processes into the organization in order to improve data excerption and apply machine learning to medical and clinical content. 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, drive decision for content acquisition, or merging big data sets to perform predictive analytics. Using visualizations tools such as Tableau to present the extracted data to be ready for consumption will be another key ability.

Proving and showcasing methodology

This person will prove the utility of new methods in deep learning, reinforcement learning, and transfer learning in a scientifically sound way. He/she will work in the areas of content generation, content summarization and question/answer creation from health content using latest ML/DL/NLP technology. He/She will work with other data scientists to develop new methods, improve existing ones and contribute to writing patents and publications

Qualifications

You have a Master’s degree (M.Sc, M.Tech etc.,) with at least 2-5 year of relevant applied experience or PhD in computer science, computational linguistics, machine learning, statistics, computational biology, bioinformatics, physics, or a related area.

Functional and Technical Competencies

Proven development experience in some relevant implementation platforms for ML/NLP tasks – proficiency in Python (preferred), SQL, R, Java

Experience working with large datasets and applying advanced algorithms specifically in the Health Sciences domains

Experience with GitLab or Github

Familiarity with ML/NLP/data science applications to some healthcare problem

Experience using *nix systems, open source software, jupyter notebook hubs, libraries and cloud computing is required

Experience with supervised and unsupervised learning: model building, validation and testing using ML algorithms such as random forest, SVM, Logistic Regression, Bayesian modeling, KNN, K-Means, LDA, etc

Experience using latest algorithms in deep learning, neural networks, reinforcement learning, transfer learning

Analytical and content strength (in DS work field): sees which DS techniques apply to the business problem at hand, able to structure the approach and a good programmer

Willingness to learn: open to feedback and development on both technical and interpersonal levels

Perseverance: does not give up when a problem is demanding, knows how to deal with setbacks

Strong communication skills: written and spoken English needs to be convincing

Entrepreneurial skills: takes the responsibility and makes it happen

Enthusiasm: has a great level of enthusiasm to inspire others

Commitment & Compensation

• Full time position
• Based on work experience

Organization Background

Elsevier is a leading provider of information solutions for healthcare professionals around the world and operates within the company Elsevier. Elsevier’s mission is to lead the way in advancing science, technology, and health. The Clinical Solutions division of Elsevier provides over 25% of the world’s clinical content, serving 9,000 hospitals globally and over 20 million healthcare professionals, including health executives, nurses, physicians, and pharmacists, by integrating evidence-based content into the care delivery process, driving better clinical decisions and improved patient outcomes. Elsevier’s ability to consistently provide its high level of evidence- based content and resources is made possible by strong partnerships with the science and health communities and leading HIT vendors, resellers, and suppliers.

Elsevier

Elsevier is a global information analytics company that helps institutions and professionals progress science, advance healthcare, and improve performance for the benefit of humanity. Elsevier provides digital solutions and tools in the areas of strategic research management, R&D performance, clinical decision support, and professional education, including ScienceDirect, Scopus, ClinicalKey and Sherpath. Elsevier publishes over 2,500 digitized journals, including The Lancet and Cell, more than 35,000 e-book titles, and many iconic reference works, including Gray’s Anatomy. Elsevier employs 7,200 people in 46 countries. Elsevier is part of RELX Group, a global provider of information and analytics for professionals and business customers across industries.

RELX Group

RELX Group is a world‐leading provider of information and analytics for professional and business customers across industries. The group serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom half are in North America. RELX PLC is a London listed holding company which owns 52.9% of RELX Group. RELX NV is an Amsterdam listed holding company which owns 47.1% of RELX Group. The shares are traded on the London, Amsterdam and New York Stock Exchanges using the following ticker symbols: London: REL; Amsterdam: REN; New York: RELX and RENX. The total market capitalization is approximately $35 billion.

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