Piper Companies is seeking a Remote Data Scientist (Credit Risk) to join a premier credit union located in Tysons Corner, VA. The Data Scientist will develop risk models to determine the credit worthiness of potential new clientele.
Responsibilities of the Data Scientist include:
- Drive monitoring and analyses of credit risk for both organic and acquired portfolios, prepare related management reporting packages, and provide insights on root causes, emerging credit trends, and implications on Allowance for Loan Losses.
- Perform business line program deep dive and monitoring on credit policy change to drive credit policy optimization and risk mitigation strategies, inform corporate strategic decisions, enable better member experience, and improve efficiencies.
- Provide ongoing or ad-hoc risk analytics to support credit or new product expansion.
- Collaborate with modeling team to build/manage risk models using both internal and external data sources, conduct risk drivers’ analysis and build and implement valuations models.
- Identify required data and work with data stewards to understand data source, ensure data quality and retrieve data on a timely basis. Contribute to credit data mart and corporate database designs.
Qualifications for the Data Scientist include:
- 1+ years of experience as a Data Scientist in a Banking or Financial Services environment
- Experience creating risk models and being hands-on with R, Python, SQL, and Tableau
- Ability to work effectively in ambiguous situations, ability to multi-task.
- Master’s degree in Math, Statistics, Economics, Computer Science, or another quantitative field is preferred
Compensation for the Data Scientist includes:
- Salary Range: $80,000-$100,000 - $40/hr – $50/hr **depending on experience**
- Full benefits: PTO, Paid Holidays, Cigna Healthcare, Dental, Vision
Data science, risk data science, data scientist, aws, amazon web services, credit cards, credit, sql, python, engineering, data, data science, product, R, tableu, banking, work from home, remote, finance, risk model, regression, modeling, risk drivers, valuation models, analytics, loan loss, credit policy
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