Remote Data Scientist, Credit bei Grasshopper Bank
Grasshopper Bank · New York, Vereinigte Staaten Von Amerika · Remote
- Professional
Grasshopper Bank is a client-first, digital bank built for the business and innovation economy, with an obsession for providing leading-edge technology, solutions-driven products and superior service through a combination of passionate people and digital resources.
We are a highly experienced team who pride ourselves on diversity of thought and perspective. Nationally chartered, our portfolio of products and services range from VC, PE & Portfolio Companies to SBA Lending, as well as direct SMB and Embedded Banking.
Our entrepreneurial drive allows us to support the growth and success of a wide range of clients at every stage of their business through inclusive partnership. We seek out team members who will enable both our organization and our people to grow and thrive through collaboration and acting with integrity and respect.
Our focus on cross-functional teamwork provides a culture where ideas are valued, accountability is encouraged, and successes are celebrated. We welcome all those searching for the opportunity to contribute to banking innovation that influences and supports the emerging digital world of Financial Services.
Our digital first approach enables our teams the flexibility to work remotely. We have offices in NYC and Boston.
What you'll do:
The Data Scientist role, reporting to the Director of Data Science, will be responsible for facilitating model development and analysis for the Digital Lending team as well as others around the bank. With data being generated from multiple systems and sources, the Data Scientist will be responsible for ensuring uniformity & accuracy of data used in analysis and model building. Working closely with the Grasshopper data science Leader, the individual will build and maintain regression & ML models for underwriting in the auto, business, and mortgage lending space. As a model subject matter expert, the individual will be expected to communicate and present their work to senior leadership on a regular basis. An ideal candidate will have significant experience working with Tableau to deliver polished production-ready analyses & presentations. The data scientist will work closely with the direct-business, BaaS, Affinity and risk teams to build scorecards & tools needed for data-driven decision making and will be a direct contributor to their strategies.
Responsibilities include:
- Work cross-functionally with data engineers, BI analysts and business stakeholders across the bank to generate models and scorecards that minimize risk, while supporting the goals of the business lines.
- Act as subject matter expert for data, outcomes, and platforms used in modelling.
- Champion data driven strategy and decision making.
- Build and implement scorecards for KYC, Fraud, Credit, and Risk.
- Develop in-house models for credit risk in both consumer and commercial business lines.
- Ensure work complies with validation and governance requirements.
- Work with BSA and Fraud Operations to identify and build tools to combat emerging trends in fraud.
- Present analysis and results to senior leadership clearly and effectively
- Develop, test, and monitor regression and ML models.
- Prepare to explain the functioning of models built and their outcomes.
- Support effort to manage model risk across the Bank.
What you need:
- 4-6 years of experience working with data and analysis tools.
- Understanding and experience in the digital banking space, especially with regards to acquisition and underwriting.
- To have delivered production risk prediction models (credit or otherwise) in the financial sector.
- Advanced proficiency in SQL, R or Python, and Tableau.
- Excellent analytical and problem-solving skills.
- Ability to communicate complicated data science topics to a wide audience
- Experience in predictive modeling.
- Ability to work independently, prioritize tasks and meet deadlines.
Experience collaborating with cross functional teams from various business lines. - Bachelor’s degree from a college or university; or related training and/or experience. Graduate degree preferred.
