VP, Data Science

Elsevier   •  

New York, NY

Industry: Energy & Utilities

  •  

11 - 15 years

Posted 175 days ago

This job is no longer available.

Elsevier is a global information analytics & technology organisation that helps institutions and professionals progress science, advance healthcare and improve performance for the benefit of humanity. Elsevier provides digital solutions and tools in the areas of strategic research management, R&D performance, clinical decision support, and professional education; including ScienceDirect, Scopus, ClinicalKey and Sherpath. Elsevier publishes over 2,500 digitized journals, including The Lancet and Cell, more than 35,000 e-book titles and many iconic reference works, including Gray’s Anatomy.

 

 

Role Value Proposition:  Driven by passion and purpose, we are looking for you to lead our global data science research and delivery team to further develop our advanced analytics capabilities while overseeing the design and implementation of state of the art data approaches which are both scalable and innovative.   This is a critical position with strategic impact on our businesses and a key leadership role in the enterprise data organization.

 

 

Key Responsibilities:  

 

  • Lead the design, implementation, and operation of a state-of-the-art data sciences platform which is scalable and innovative in the manner it extracts, manages and analyzes data with an emphasis on aligning to key business objectives

  • Oversee the efficacy of advanced analytics and statistics efforts including Machine Learning, Natural Language Processing & Artificial Intelligence.

  • Provide strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of next generation data practices.    

  • Develop innovative approaches to linking internal systems with external data

  • Collaborate with stakeholders, partners, and clients while activing in an advisory capacity in supportive of client priorities, requirements and objectives

  • Responsible for development of analytic problem solving methodology to be deployed enterprise wide

  • Responsible of ‘first of a kind’ research and develop innovative approaches to leverage external data

  • Accountable for developing and sharing new developments in academic research within data science and applied statistics field including further develop university partnership

  • Responsible for talent development for data science practitioners

 

 

 

Essential Business Experience and Technical Skills:

  • Minimum of a Master’s degree in statistics, mathematics, computer science or a related discipline emphasizing scientific inquiry; PhD preferred
  • 10+ years of experience working in a field using machine learning, other predictive modeling techniques, engineering, statistics, mathematics, computer science or related field
  • A proven leader who has the foresight and business context to provide optimal data-science vision, strategy and business practices for the organization   
  • Understanding of statistical significance, confidence intervals, uncertainty estimation and diligent application of the scientific method
  • Extensive background and track record in statistical methodologies as well as data mining and machine & deep learning strategies, and proven experience validating models against experimental data
  • Previous experience and success in both managing and leading a team
  • Proficient written and verbal communication skills, demonstrated success in communicating and presenting data and concepts to clients and audiences with varying backgrounds and visualizing data to stakeholders
  • Subject Matter Expertise (SME) with data analytic, scientific computing and statistics packages
  • Extensive background and track record in statistical methodologies as well as data mining and machine & deep learning strategies, and proven experience validating models against experimental data.

 RES000UB