Deputy Director Data Science
BayerUpdate time: October 21,2019
Job Description

YOUR TASKS AND RESPONSIBILITIES

 

The primary responsibilities of this role, Deputy Director Data Science, are to:

 

 

  • Own Machine Learning (ML) & Artificial Intelligence (AI) analytics COE for US Data Gen & Observational Studies

 

    • Drive development of analytical methodologies, from hypothesis development to insight generation

 

  • Own ML & AI process

 

    • Drive development of major deliverables of proof of concepts and use cases
    • Uncover business trends and opportunities that can be realized by the BUs e.g. triggers
    • Support DA team with ad hoc analytics
    • Directing third parties retained to support analytics, research, and consulting efforts, such as onshore and offshore resources

 

  • Partner with key stakeholders

 

    • Partner with DG&OS Research and Field teams to help define business questions and translate them into business requirements
    • Provide direction to technical resources and vendors to support translated business requirements into design, data and technical specifications and generate insights
    • Develop recommendations and provide consulting to key stakeholders and their extended teams based on insights driven by related analytics

 

  • Develop competencies and talents

 

    • Identify opportunities for developing colleague skills and competencies and recommend training opportunities
    • Ensure continuous improvement of department competencies around ML &

 

  • AI Analytics

 

    • Be an expert in ML & AI

 

 

 

WHO YOU ARE

 

Your success will be driven by your demonstration of our LIFE values.  More specifically related to this position, Bayer seeks an incumbent who possesses the following:

 

 

Required Qualifications:

 

 

  • Master’s degree, with major in Data Science, Statistics or related,

 

  • 5+ years of overall full-time work experience

 

  • Strong experience in Machine Learning and Artificial Intelligence especially in Regression, Gradient Boosting, Random Forest and Neural Network model.
     
  • Strong experience in statistical programming languages (i.e. SAS, R, Python)
     
  • Strong experience and knowledge of U.S. healthcare insurance claims data, across multiple therapeutic areas and brands pertaining to Bayer’s business, including but not limited to IBM Watson MarketScan, Optum Clinformatics, Optum Humedica EHR, Flatiron HER
     
  • Strong display of strategic thinking and planning experience, as expressed through leadership in respective projects and presentations
     
  • Knowledge of therapeutic areas relevant to Bayer’s U.S. business
     
  • Client focus and responsiveness
     
  • Record of professional success, demonstrated through above-average performance reviews, promotions, and relevant "extracurricular" activities/ engagements
     
  • Strong verbal and written communication skills, as demonstrable in oral management presentations, succinct PowerPoint stories and layout, as well as structured syntheses and recommendations
     
  • Effective project management skills, as demonstrated by on-time, on budget project delivery
     
  • Demonstrated leadership skills, including team leadership, thought leadership, and leadership awareness
     
     

 

Preferred Qualifications:

 

  • Ph.D

 

  • Knowledge of SAS’s Visual Data Mining & Machine Learning (VDMML) tool

 

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