Our team at Elsevier is building the world's highest-accuracy comprehensive citation graph. The citation graph is constructed automatically from data originating from diverse scholarly sources, and is a major building block of widely-used products including Elsevier's Scopus. We are looking for a Data Scientist with 1-5 years of experience, especially in NLP and Text Analytics, to be a part of our core team.
- Help advance the development of our models for disambiguation, tagging, linking, clustering, and deduplication. Our goal is industry-leading accuracy of the citation graph and the systems that build it.
- Develop a deep understanding of our algorithms and systems, and develop a deep understanding of the scholarly data we work with. This is necessary to enable identification of opportunities for fundamental improvements in our algorithms, and to enable identification of root causes of problems.
- Work with our content evaluation team to build large-scale gold sets that are the basis for measuring and improving the recall and precision of our systems. This includes devising new ways to sample data, to focus on areas targeted for improvement.
- Work on varied projects to extend our systems to new content types and new application areas.
- Advance the automation and reliability of our core data science processes.
- Work closely with our software engineers to drive experiments, implementations, optimization, and new features.
- Work independently with end-to-end ownership of tasks.
- Work cooperatively with other team members in Bangalore and in remote locations.
Skills and Behavioral Attributes:
- An M.Tech/B. Tech in Computer Science, Data Science, Information Systems, Applied Statistics, or related disciplines with sound technical expertise relevant to the areas mentioned above.
- Experience working on data science projects that have reached the commercial production stage.
- Experience with Python/Perl, Java, and databases.
- Comfortable working both cooperatively and alone.
- Structured problem solving skills to translate problems into solutions.
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 email@example.com or if you are based in the US you may also contact us on 1.855.833.5120.