Overview

Are you a Senior Machine Learning Scientist and do you know of the state-of-the-art tooling in capturing textual content and translating human annotations to machine models? Have you industry experience in working with big data? We have the right opportunity for you!
In line with the Elsevier corporate strategy of greater content volume, types and sophistication, the services that Elsevier provides are becoming increasingly dependent on Smart Content. We are therefore looking for a Machine Learning Scientist who can focus on designing and creating systems that enable machine learning in the context of article submission systems and other systems where authors provide scientific content to be published by Elsevier journals.
Focus of the position
As a Senior Machine Learning Scientist, you will be working with our business units on developing services that analyze, annotate and structure content found in scientific articles. We want to develop automated text classification and entity linking targeting specific problems in scientific manuscript structuring, author and reference identification. Ultimately, machine learning tools may suggest annotations and structured meta-data that are as good as human-generated data and even replace human annotations. Our solutions depend heavily on concept indexing or annotation, relationship extraction, extracting data from formatted text, images, mathematical expressions and tables. As a Senior Machine Learning Scientist, you will have industry experience solving content analysis problems using supervised or unsupervised machine learning methodologies, you know of the state-of-the-art tooling in processing textual content at a large scale and be familiar with analyzing image data. You have a good understanding of the current Machine Learning libraries and have used at least some of them, solving real life problems. You are a hands-on person that does not care about Java or Python but about the right approach to the problem.
Working together
You will be working in Elsevier Operations with a varied and cross-functional team of IT and product colleagues to pilot and develop new methods of extracting and surfacing information relevant to our customers for new product development. When successful, the Senior Machine Learning Scientist supports the implementation of industry-scale high-quality production systems. You will work closely with both the domain subject matter experts and NLP teams.
Main Activities and Responsibilities
Develop and apply machine learning methods in projects across Elsevier
• The suitable candidate will bring active experience in information extraction from textual and image data and work on the projects that require large data processing
• Applying and developing machine learning techniques, the Senior Machine Learning Scientist will drive the implementation of automated recognition processes, to improve them in cost and time-efficiency
• Using the available data, the Senior Machine Learning Scientist will actively promote new ideas to enhance our competitive offerings
• The Senior Machine Learning Scientist will actively contribute to product and operational content strategies by identifying and ingesting new technical capabilities to forward Elsevier mission of leading the way in advancing science, technology and medicine
Serve as internal and external specialist on Machine Learning techniques
• The suitable candidate will serve as the Machine Learning expert in the Content and Innovation team
• The Senior Machine Learning Scientist will also be able to act as a liaison between IT developers and (content) subject matters experts, translating information needs into software development

Company:

Elsevier

Qualifications:

Qualifications
• Master or PhD degree in Computer Science, Engineering, Statistics, Data Science, Computational Linguistics or an associated area
• A creative problem solver with a strong knowledge of statistics, text analytics and machine learning methods and strategies
• Industry experience is strongly preferred
• Ability to drive new developments and implement process changes and disruptive technologies in the organization
• Good communication and documentation skills with the ability to convey complex technical concepts to non-technical professionals
• Experience working with a variety of stakeholders at the mid and senior management level
Technical skills
• Strong experience with applying Machine Learning methodologies, such as SVM, Neural Networks or other stochastic models for classification or CRF- type models for sequence recognition/ prediction
• Strong experience with Natural Language Processing. Familiarity with image analysis is a plus.
• Scientific software development experience, preferably in Python or Java.
• Handling XML data, and experience using *nix systems, open source software and libraries
• Experience with Spark is a plus
• Familiarity with agile software development
• Support technical scoping, design solutions requirements and testing, maintain documentation and perform code reviews
• Know how to improve efficiency of existing code and optimize performance

Educational level:

Master Degree

How to apply:

Please mention NLP People as a source when applying

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About Elsevier

A leading provider of science and health information, Elsevier partners with experts around the globe to develop world-class content, delivering it in ways that fuel discovery, drive innovation and improve health care. Our global community comprises over 7,000 journal editors, 70,000 editorial board members, 300,000 reviewers and 600,000 authors. They are scientists and clinicians; authors and editors, professors and students; information professionals and decision makers.

We are a global company headquartered in Amsterdam, employing more than 7,000 people in 24 countries. Elsevier's roots are in journal and book publishing, where we have fostered the peer-review process for more than 130 years. Today we are driving innovation by delivering authoritative content with cutting-edge technology, allowing our customers to find the answers they need quickly.