DataRobot believes that automation of data science workflows will transform not only the data analysis and business intelligence industries, but every industry.  The increased accuracy and radically decreased costs that automated machine learning brings will allow every enterprise to be an AI-driven enterprise.

We are seeking an extremely talented Banking and FinTech SME to help our team of world-class team bring automated machine learning to companies around the globe.

 
Responsibilities 
  • Working with banking and fintech vertical SME's, develop detailed use cases, demo scripts, materials for webinars demonstrating DataRobot value prop
  • Prepare banking/fintech use case demo datasets using available third party data (e.g. FactSet, Demyst, publicly available), synthesizing training data as necessary
  • Develop artifacts to brief CFDS's and accelerate/improve quality of PoC's (e.g. use this fraud data to develop this predictive model)
Requirements
  • Strong technical skills (data manipulation, feature engineering)
  • Deep understand of machine learning models/techniques
  • Experience working with large/complex datasets and building predictive models
  • Banking/Fintech experience or business aptitude and eagerness to learn about banking/fintech space

 

Individuals seeking employment at DataRobot are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.

Business

 

The DataRobot Business Team brings an algorithmic approach to everything that we do in the organization—from product development, go-to-market strategy (GTM), marketing, sales, and client engagement. We are a data science driven organization, tracking high quality historical data, inducing a metrics and monitoring process, analyzing wins and losses, and finally, collaborating with all other functions to develop a winning business strategy. If you are an analytical problem solver and love to work with people across teams, come talk to us.