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Customer Facing Data Scientist – Financial Markets 1349 views

The Customer Facing Data Scientist is critical to making their customers successful. An ideal Customer Facing Data Scientist candidate should have strong fundamentals of applied data science in business setting, and should enjoy communicating and evangelizing data science solutions to business stakeholders.

Roles And Responsibilities

  • Product
  • Representing the DataRobot product from a technical standpoint to customers – including demonstrations, conducting proof-of-concept trials, helping clients evaluate success criteria, and training users
  • Providing the customer’s point of view to DataRobot’s Product team, informing the direction of future product feature development
  • Data Science
  • Enabling customers to solve complex data science problems using DataRobot – including problem framing, data preparation, model building, model deployment, model management, and output consumption
  • In some cases, executing data science workflows for customers
  • Providing data science knowledge and expertise as a trusted advisor to the client
  • Project management
  • Conducting and managing data science projects with customer’s vision of success in mind
  • Collaborating with Sales, Field Engineers, and the rest of the DataRobot team to identify the best possible resources to move forward customer’s projects
  • Leadership
  • Building a long-term trusted relationship with the customer so that the customers can be led towards success
  • Understanding and empathizing with customers’ pain points of building AI solutions
  • Qualifying opportunities where DataRobot can be a suitable fit and thus making DataRobot more efficient
  • Presenting DataRobot in industry conferences as well as creating powerful technical content for marketing purposes

On a day-to-day basis, CFDS work side-by-side with the Sales, Account Management, and Field Engineering teams to help our customers achieve their goals with DataRobot. Internally, CFDS act as the voice of customer to the Product, Engineering, and Marketing teams.

Main Requirements

    • 5+ years of experience in financial markets
    • Experience in performing time series analysis
    • 3+ years of real-world business experience in a data science role
    • Hands-on experience building and implementing predictive models using machine learning algorithms
    • Strong customer interaction experience
    • Strong project management skills
    • Excellent organizational, communication, writing and interpersonal skills
    • Familiarity with a variety of technical tools for the manipulation of datasets
    • Fluency with scripting (Python / R)
    • Going onsite to customer locations in New York City and the broader Tristate area. Up to 10% travel outside the Tristate area.

 

Desired Skills

  • Familiarity with consultative sales process in the analytics marketplace
  • Familiarity with Hadoop and related Big Data technologies
  • Experience dealing with complex customer organizations

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