W1siziisimnvbxbpbgvkx3rozw1lx2fzc2v0cy9jbnrlbgxldgvjig5ldy9qcgcvbmv3lwjhbm5lci1kzwzhdwx0lmpwzyjdxq

VP of Data Science - Venture Capital Group

  • Location

    Chicago

  • Sector:

    Data Science

  • Job type:

    Permanent

  • Salary:

    Very Competitive (TBD depending on candidate)

  • Contact:

    Rebaz Has

  • Contact email:

    Rebaz@intelletec.com

  • Job ref:

    DS901

Rare opportunity to join one of the world’s leading VC firms focused in the tech space. The role is part of a new centralized analytics team that will interact with all the leading tech firms in their portfolio.

 

This group will be highly-visible across the company and will be responsible for transforming 6+ Petabytes of diverse data, spanning various industries, into actionable insights, products & services.

 

You will have direct involvement with several industries including: Healthcare, Finance, Trucking, Talent Management, Hospitality, Sports, Legal and News Media among others. This is an extremely rare opportunity to be a part of a success story from the ground up, with the feel of a Start-Up, but backed by the strong leadership and resources of leading VC firm.

 

SKILLS AND EXPERIENCE:

  • PhD or Masters in a Quantitative field
  • 5+ years’ experience working with advanced Machine Learning methods. Neural networks, Deep learning & NLP methodologies a big plus
  • Experience with large datasets & distributed computing (Hive/Hadoop, Spark)
  • Experience with statistical tools or packages (R / Python et al)
  • Tensorflow & Keras a bonus
  • A highly motivated go-getter, capable of wearing multiple hats
  • The ability to deal with ambiguity in a fast-paced dynamic environment. You are not afraid to fail, but fail fast, and learn from the mistakes, making everyone around you better for it
  • World Class communication skills
  • Ability to communicate complex topics to senior executives in simple terms

 

THE ROLE:

  • Speaking to, presenting to, and understanding a wide range of stakeholders, from CEOs to Engineers to End-users and Customers 
  • Apply advanced Machine Learning Methods for the purposes of actionable business insight
  • Build out a world class data science team
  • Deliver a data model for our first product within the first 60 days
  • Work with the Chief Data Architect to build the data system over the first 180 days
  • Review the portfolio company data as they roll out new disruptive new products and look for product development opportunities
  • Work with Product Managers to create new product hypothesis for testing
  • Look for data that may have meaningful correlations to public traded equity