Data Scientist I

Data Scientist I London, England

Elsevier
Full Time London, England 69519 - 69906 GBP ANNUAL Today
Job description

Are you eager to create the best possible data science solutions that help solve customer (e.g. researchers, authors, editors) problems?
Do you want to develop decision support tools to help making faster and better decisions?
About our Team
This is an exciting opportunity for a data scientist to join a highly collaborative product data science team that works within the Elsevier Academic & Governments product group. The team helps to make the most out of Elsevier’s high-quality scientific content, data, and customer understanding. Embedded in the product teams we solve customer problems by creating recommendations and we help make faster and better decisions.
About the Role
As a Data Scientist I you should understand the best practices and processes and be able to execute them independently, and review results with supervisors. Individuals in this role should work with leads to define project scope, and then execute the necessary methods to develop, test and deliver outcomes.
Though the role will be based in London or Amsterdam, you will be working with colleagues in locations in the US and rest of Europe.
Responsibilities
  • You will be accountable, together with the rest of the team, for understanding product objectives, key results, and data science specific requirements.
  • You will develop, with senior guidance, algorithms and machine learning techniques and apply them to a wide variety of tasks such as NLP solutions and recommender systems. You will do so primarily by providing support to more senior Data Scientists who in return will provide you mentoring and development support. You will pull and clean data, and build and maintain existing models.
Requirements
Essential
  • Demonstrate building competency of machine learning fundamentals, including model training, testing, and validation.
  • Proficient in standard coding languages (e.g. Python / scikit-learn, Spark / Spark-sql, Kedro, MLFlow).
  • Basic experience of feature engineering, data preparation, and data pipelines.
  • Able, with senior guidance, to run Machine Learning, Data Mining, and/or Statistical methods already in use to build or update solutions.
  • Able to independently support project management of small scale projects and with senior guidance support more complicated project steps.
Nice to have
  • Basic knowledge of neural network/deep learning approaches to information retrieval
  • Knowledge and preferably some experience with recommendation systems.
  • Knowledge about the research ecosystem, experience with academia or other professional research.
You are someone who
  • Enjoys working in a collaborative and cooperative environment across technical disciplines and skill levels
  • Is willing to take risks in learning new things and go beyond their comfort zone, mistakes are learning opportunities
  • Is able to prioritise own work while keeping team and product priorities in mind
  • Makes data science repeatable, follows existing procedures and be methodical in creating new ones
  • Is able to troubleshoot (own) projects and resolve issues.
Preferred academic background and professional experience
  • Undergraduate degree in a relevant field and some relevant work experience.
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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. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form:
https://forms.office.com/r/eVgFxjLmAK
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Data Scientist I
Elsevier

www.elsevier.com
Amsterdam, Netherlands
Kumsal Bayazit
$2 to $5 billion (USD)
5001 to 10000 Employees
Subsidiary or Business Segment
Publishing
1880
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