Job description
This person will:
- Actively contribute to build analytics and measure KPIs on content quality by developping big data analytics workflows, using SPARK and other technologies in our Databricks clusters and EMR.
- Actively contribute to build content improvement methods ingesting and linking content from different sources, using various techniques from machine learning (ML), natural language porcessing (NLP), taxonomies and linked data.
- Actively contribute to product and operational content strategies by identifying new technical capabilities for big data workflows and content transformation automation. Using visualization tools to communicate analysis will be another key aspect of the work.
Recommended Skills and Education:
Technical skills: Data Science and software development experience in Python or a curly brace language as well as scripting abilities. Writing queries, handling data (ETL), and experience using *nix systems, open source software and libraries. Is able to write design specifications, tests, maintaining documentation and perform code reviews. Industry experience in ML and large-scale data mining is a big bonus.
Interpersonal Skills: Be able to communicate clearly with various stakeholders and explain difficult or sensitive information.
Education: University graduate (Master or PhD level) in computer science, computational linguistics or an associated area. Industry experience in Machine Learning, information clustering and large-scale data mining is a big plus.
-
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 protected] or if you are based in the US you may also contact us on 1.855.833.5120.
Please read our Candidate Privacy Policy
