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Customer Data Scientist / Sales Engineering

Company Overview

H2O is the premier open-source machine learning platform transforming how machine-intelligence applications are built. With H2O, data scientists take both simple and sophisticated models to production from the same interactive platform they use for modeling, at enterprise scales. Our customers have built powerful domaterin-specific predictive engines for recommendation, pricing, and outlier detection in fraud & insurance. The H2O.ai team is a mix of Software, Math, and Data Science people working together with the open source community to build H2O.

Job Summary

Knocking down technical barriers to the adoption of H2O.ai’s products and services is the main responsibility of a Customer Data Scientist at H2O.ai.  This includes being the technical part of the sales team focused on presenting H2O.ai’s technology to help solve customers’ critical business problems. 

Another critical part of the role is ensuring the success of existing customers along with expanding the usage of H2O.ai’s technology by discovering additional use cases within a customer’s organization.  In order to do this successfully an understanding of a few key technologies is important, namely, machine learning, R, Python, databases, Hadoop and Spark.

Customer Data Scientists engage with the data scientists at prospects and customers to work in different industries and different problems every day.  This is a hands-on data scientist role.  You are not just doing slide-ware, you’ll be building machine learning pipelines and working with customer to architect enterprise-scale smarter applications for large organizations.  Experience seeing the entire lifecycle from conception to design to technology evaluation to pilot program to implementation to maintenance and support is crucial.  This person will interact closely with H2O.ai Engineering to provide valuable optimization feedback from customers that will make its way back into H2O products.

Responsibilities

  • Engage with sales prospects where you prepare and present H2O.ai’s technology along with addressing any technical questions that come up during the sales cycle, including executing machine learning proof of concepts to demonstrate sped and prediction technology
  • Support the technical needs to existing customers discovering additional use cases for H2O.ai’s technology
  • Work closely with the product management and engineering teams to align customer requirements to future versions and products
  • Have a deep understanding of H2O.ai’s technology and a willingness to learn new technologies when needed
  • Manage technical sales process for numerous customers, day to day
  • Map customer requirements to current and future offerings
  • Own the technical sales process from introduction meetings (net new sales) through post-sales (customer satisfaction, upselling and subscription renewals)
  • Educate prospects on the business vale of H2O.ai’s offerings
  • Drive progress towards successful sales, in concert with Account Executives
  • Focus on customer satisfaction and success

Qualifications and Skills   

  • 2+ years’ experience with performing customer facing activities as part of a pre-sales team or professional services team
  • 2+ years’ experience with Machine Learning and Data Mining
  • 2+ years using R or Python for data analytics
  • 1+ year working with data in Hadoop and /or Spark ecosystem
  • Demonstrable ability to create and give technical presentations and demos
  • Comfortable presenting to large audiences (on-line and in-person)
  • Excellent communicator with experience presenting to a wide range of audiences
  • Comfortable articulating technical problems at a business value level
  • Ability to lead in-person and remote troubleshooting sessions with various stakeholders including data scientists, administrators, developers, and architects.

Travel Requirements

  • 50% travel, mostly within major geographic territory of North America
  • Travel requirements may reduce as remote troubleshooting and optimization proves effective

Education

Requires a Masters’ degree or higher in the area of data science, computer science, statistics, mathematics, physics, engineering, operations research or other quantitative field

 

This is an excellent opportunity to learn about machine learning as a member of our world-class team. 

 

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