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Data Scientist

Full Time

Anywhere across USA

As a Data Scientist, you will be responsible for ensuring the successful implementation and usage of Scienaptic’s platform across dozens of clients. You will be working with some of the best-in-class Coders, AI/ML Scientists and Business Analytics Consultants in an environment which will encourage you to contribute widely to functional and technological aspects without worrying about conventional job silos.


  • Design tools and monitor the credit performance on client’s portfolios and intervene as needed

  • Identify common risks and possible solutions across Scienaptic’s clients

  • Develop insights to inform strategy improvements and new product use cases

  • Become the resident SME for Scienaptic’s solution and optimal strategic use

Skills & Competencies

  • At least 2 years’ experience in a Credit Risk analytical role, ideally for a Fintech or financial institution focused on consumer or small business lending

  • Expertise in credit risk management for revolving / non revolving products (e.g., lines of credit, term loans)

  • Prior experience of working with at least one of the 3 major US credit bureaus

  • Strong analytical skills to understand the business process needs and translate them to system requirement specifications

  • Proficiency with one or more database querying tools (SQL, R, Python)

  • Proficiency with analytical tools and visualization software (e.g., Excel, Tableau, MongoDB)

  • Attention to detail and quality of the deliverables and a growth mindset

Scienaptic is the world's leading AI-powered Credit Underwriting platform. Designed by seasoned Chief Risk Officers, its platform is creating industry-leading business impact in terms of lifts such as higher approvals (15-40%) and lower credit losses (10-25%). Last year alone, Scienaptic helped financial institutions evaluate 45 million credit applicants and approve over 15 million of them. Scienaptic's clients include Fortune 100 banks, credit unions, regional banks and FinTech's.

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