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Data Research & Analytics
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Elsevier
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RES0019M Requisition #

Researchers seek a digital environment where ideas can be exchanged, examined, and applied with tools that empower scientific, medical and technical knowledge.  Elsevier’s research platforms allow them to find and analyse data from over 5,000 publishers via Scopus; access the leading ebooks and journal articles published by Elsevier on ScienceDirect; and manage their research and showcase your profile via free services on Mendeley.  These platforms make data and content easier to search, access, analyse, and share.

 

The primary focus of the Principal Data Scientist is to support in creating a vision, roadmap and implementation plan for search and at times recommendation functionalities and data science needs within the Researcher Platforms group of Elsevier.  These outputs will be utilized across the Elsevier organization which will include the integration of various data types like scientific (publications, awards), usage, and news to identify monetization opportunities across Elsevier’s platforms. 

 

The Principal Data Scientist will design, implement and evaluate test frameworks, data cleansing, linking and knowledge mining techniques that will allow integrated use of the linked data and support the Elsevier product vision. The role includes responsibility for defining and executing an implementation plan based on good understanding of business priorities, key performance targets, data standardization - and scalability requirements.  The Lead Data Scientists experience and understanding of Information Systems (e.g. information retrieval, recommender systems, search engines) and Machine Learning will enable Elsevier to turn product ideas into potent software solutions.

 

The role holder will at times represent Elsevier internally and externally at meetings and contribute to the research community with the creation of content/publications within areas of relevance and actively support events or initiatives within the community.   The role will also take responsibility for:

 
  • Vision and strategy development – support in the definition, development and dissemination of the Elsevier Data Science strategy; ensuring the capabilities created are well aligned with the functionality needs derived from business/product development strategies. Provide input to senior executives on Data Science related scientific developments, opportunities, strategies. Contribute to Data Science related strategy developments across Elsevier businesses. Actively seek opportunities to share Data Science capabilities e.g. by building strong relationships with other parts of the business with similar expertise.
 
  • Roadmap planning - Lead the collection, assessment, linking and filtering of data (content, usage, and transactions) related business needs and priorities across Elsevier related product groups.  Lead the application of machine learning principles in order to develop signals consumed by multiple Elsevier products across the organization.  Lead the continuous engagement with senior executives and Big Data stakeholders across Elsevier to get buy-in and support for the roadmap.
 
  • Technical expertise:  Develop predictive modelling using machine learning and statistical techniques (for example, but not exclusively, GLM, NLP, Deep Neural Networks, SVMS, Naïve Bayes, Decision trees, etc.).  Demonstrating and mentoring others to the inner workings of such techniques and how they have been applied to generate value.
 
 
 
You will bring:
 
  • Technical scientific background - You must possess a unique blend of business, technical, and scientific expertise; a big picture vision, but yet also have an eye for detail. You must have the drive to make your vision into a reality, both from an acceptance point of view — being able to sell your idea to senior management, based on metrics driven arguments combining analytics and insights gained from market feedback — and be able to implement your ideas.
  • Technology - You should have a working knowledge of high performance, high volume, and multi-tiered, service-oriented web architectures and be comfortable in engaging closely with development teams to communicate business needs and understand technical tradeoffs. You should have an understanding of conceptual data modelling, with the ability to map complex business rules and models into coherent and flexible data models. You should be comfortable with agile development practices with an emphasis on roadmap development and prioritization
  • Leadership – leadership and mentoring capabilities; creates a vision, sets the pace, motivates, and creates a structure through which sustained results can be achieved.  Can provide vision, clarity and guidance around the data science strategy; using appropriate interpersonal styles and methods to achieve business goals.
  • Customer Focus - You must enjoy spending time with internal and external stakeholders to understand their problems, and find innovative solutions to solve these within the context of the broader product strategy.
  • Communication - You must be able to communicate with all areas of the company and build strong relationships with stakeholders and the search and data science groups.  Outside of the business you have credibility and are seen to be a thought leader within data science by the research/academic community
  • Analytics - You must have the drive to make your vision into a reality, both from an acceptance point of view — being able to sell your idea to senior management, based on data driven arguments combining analytics and insights gained from market feedback and being able to implement your ideas
 
Experience and skills:
 
  • MS or PhD degree in a statistics, mathematics, pattern recognition, machine learning or data science related domain
  • 8-10 Years of industry experience in delivering  commercialized products
  • A polyglot; comfortable writing code in a variety of languages such as C/C++, Scala/Java, Python/R/Julia and/or SQL
  • Experience with big data technologies (e.g. Hadoop, MapReduce, Scalding, Spark) within an Agile development methodology
  • Proven Manager and people operator that puts the team first
  • Proven leadership capability in roles towards data analysis, quality control
  • Experience interacting with senior executives and CIOs/COOs, explaining them business & technical choice points and facilitating decisions
  • Strong analytical skills and ability for conceptual & strategic thinking
  • Proven capability to learn about new techniques and technologies whilst simultaneously applying in product or analytics
  • Excellent communication and negotiation skills, both verbal and written, and the presence to interact with and present to senior executives
  • Extensive experience with and knowledge of scientific publishing, infrastructure development and complex databases systems
  • Ability to anticipate and manage potential points of conflict, balancing the interests of different groups against strategic objectives
  • Broad overall end-to-end operations knowledge: processes, tools, suppliers and systems
  • Good understanding of overall business drivers and product development drivers
  • Good understanding and experience of the full project life-cycle, management and structured development processes

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