Data Scientist

Job Description

Data Scientist position at ElsevierIn 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 looking for ambitious and agile data scientists that would like to work on designing and creating systems that apply machine learning and information extraction techniques. Also, he / she can provide expertise, advice and support in the implementation of a wide quality management framework for the annotated content.As a Data scientist you will be working with our business units on developing our content and information offering to end customers. These services rely on existing text and data mining processes. These processes are a blend of manual and automated information extraction. We want to introduce more automation to these processes by capturing human inputs and learn from those. Also, we want to assist human extraction by enhancing automated extraction processes targeting specific problems such as table extraction, image extraction and interpretation, tackling the translation of non-English content and improved filtering of information for relevance. Ultimately, machine learning tools suggest enrichments that compete with human-generated data or even replace human excerption efforts. As a Data scientist you know of the state-of-the-art tooling in capturing content and translating human annotations to machine models, such as sequence models cast in HMMs, CRFs or similar methods, and also have had some exposure to deep learning techniques.In this role: You are a hands-on person that does not care about Java or Python but about the right approach to the problem. 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 Data scientist supports the implementation of industry-scale high-quality production systems. You will work closely with domain subject matter experts responsible for quality assurance of annotations done manually by suppliers. You will obtain relevant product and content knowledge to understand current quality assurance procedures. You will also use your NLP/ML knowledge and the group s expertise to help developing best practices for quality assurance of data extraction and annotation done manually by external suppliers or internally by automatic processes. You will play a key role in applying your knowledge of NLP/ML to build a bridge between stakeholders involved in application of NLP/ML and the quality assurance of manual annotation. In this context it is important to communicate efficiently with these stakeholders, and link product content and quality knowledge with development and application of NLP/ML methods.How to succeed You have M.Sc with at least 2-5 year of relevant applied experience or PhD MSc or PhD with excellent academic results in the field of Computer Science, Machine Learning, Mathematics, Statistics, or other quantitative fields Experience in working in an Agile/Scrum way would be great Machine Learning: Deep Learning, Classification, Regression, Clustering, Text Mining. You have an excellent understanding of Neural Networks, Random Forests, Logistic Regression, SVM, KNN, K-Means, LDA, etc Programming Languages: Strong hands-on in Python or Java 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-----------------------------------------------------------------------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 accommodationsrelx.com or if you are based in the US you may also contact us on 1.855.833.5120.Please read our Candidate Privacy Policy,

Keyskills :
machine learningdeep learningsubject matter expertspythondata miningspoken englishdata extractionsqlneural networksanalyticsbusiness unitsdata analysis