Cognical, dba Zibby, is a mission-driven financial technology company with big plans to remake finance from the bottom-up. We build payment products that give 48% of the US population with low and evolving-credit a way to get the products they need, from the retailers they choose, online or in-store. Zibby’s goal is to graduate successful payers to lower payments. We are well-funded by top VC’s and led by team of experienced entrepreneurs.
Zibby is looking for a Data Scientist that will help us discover the information hidden in vast amounts of data and help us make smarter decisions to deliver even better products. One of the primary focus will include solving one of the world’s largest problems: financial inclusion. Our team is working on cutting edge work in the field of Data Science and Machine Learning using unique data to give people in emerging markets access to credit. Our Data Scientists will partner directly with Credit, Risk, Software Engineering, and BI Teams to develop and iterate models that promote our vision of financial access for a billion people in emerging markets around the world. The right candidate will have a passion for discovering solutions hidden in large data sets and working with team members to improve business outcomes.
- Develop, deploy and maintain a credit-based model (or models) from scratch or integrating new data sources in our existing underwriting models.
- Work directly and collaborate with the Risk Team to understand the performance, risk, and financial impact on the portfolio, iterating the model to include new information, data and feedback.
- Monitor model performance once deployed and recommend rapid iteration if necessary.
- Contribute and share your findings and knowledge of credit and/or risk modeling with all appropriate cross-functional teams.
- Partner with the Engineering team to develop, test and deploy credit models.
- Pull data directly from DB, handling all the ETL to running the model to obtaining a decision.
- 5+ years of experience in a Data Science role or equivalent position
- Must have 5 years of consumer lending experience
- 3+ years of experience in building fraud, credit, or risk models
- A Masters or PhD in a quantitative field
- Fluent in Python and packages related to machine learning
- Excellent communication and interpersonal skills
- High attention to detail and very organized, with keen analytical and problem- solving skills
- Ability to function independently and work on a team in a fast-paced startup environment
Experience with maintaining data science models in a production environment NPV modeling, Response Modeling/Propensity Modeling, Collections modeling/experience risk modeling.