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
- 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