VP Data Science

ExecuNet

Job Description

What You’ll Do:

Data science is at the core of what we do at Company. We collaborate with engineering, product, and other teams to contribute insights and data science best practices to all parts of the business.  You will have the opportunity to lead a team of Machine Learning Engineers 

  • Deliver machine learning algorithms to solve business specific problems mapped to use cases across multiple industries 
  • Lead and mentor a team of Data Scientists and collaborate with Functional Architects, Technical Architects, and Solution Managers to understand business needs and devise possible solutions
  • Research and develop statistical learning models while keep up to date with latest technology trends
  • Implement new statistical or other mathematical methodologies as needed for specific models or analysis
  • Optimize joint development efforts through appropriate database use and ML model designs
  • Communicate results and ideas to key decision makers

Responsibilities:

  • Build a diverse data science team and maintain an inclusive environment
  • Mentor team members
  • Define overall strategy in partnership with senior executives and peers across the organization
  • Make data, data science and AI technology and platform decisions
  • Communicate effectively with executives and line-of-business end-users to discover pain points and use cases, lead project definitions, and convey the business value of the project
  • Maintain a portfolio of decisions tied to value statements and monitor as metric system to show success of team
  • Create a self-funded team by generating cost savings and new revenue opportunities.
  • Be the external face for data science and AI by presenting externally at relevant conferences and media events
  • Provide opportunity for team to maintain their current skills and develop new ones both in and out of their domains
  • As the senior most expert in the company, you will maintain your hands-on skills and expertise as well as the relevancy of your skills by staying up to date on current tools, methodologies and processes.
  • Provide guidance on algorithm selection, library selection for the Data Science team
  • Design a modern MLOps workflow process for model maintenance
  • Own Company’s internal Data Science model library

Qualifications:

Preferred:

  • 10+ years of professional experience driving process re-engineering, improvement and automation initiatives with demonstrable business results and proven experience in leading teams and organizations 
  • Extensive knowledge with cloud technology, e.g SaaS, PaaS and IaaS Exposure to Python, .Net, SQL, Java or JavaScript, and application API development Experience with Cognitive, Machine Learning, Natural Language Processing (NLP) 
  • Bachelors, Masters or PhD in Data Science or related quantitative field 

Job Requirements

 

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