Data Scientist - Fraud (Remote)

SUMMARY:

Under the supervision of the Fraud Strategy Manager, the data scientist will assist in building, managing, and implementing statistical models and apply segmentation techniques like CART/CHAID to identify new opportunities for business.  The Data Scientist will work closely with cross functional partners across Fraud, Marketing, Product, Technology and Operations to identify analytical and model development opportunities. In addition, the data scientist will assist in ensuring internal controls and documentation is complete and accurate. The data scientist will support the Model inventory management process as well as other governance initiatives across the bank.

PRINCIPAL DUTIES AND RESPONSIBILTIES:

• Development and implementation of the In-Business Model Risk Management program to identify, monitor and manage model risk.
• Responsible for model development documentation (MDD) for both in-house and vendor models.
• Responsible for model monitoring for DBU fraud models.
• Develop and review model performance monitoring reports, interpretating and analyzing results.
• Design effective model operational controls with model users. 
• Manage resolution of findings, recommend management actions plans and tracking progress.
• Support management of models including identification of models, documentation of model design, assumptions/limitations, output and uses and input processing.
• Collaborate with model owners to ensure models are business driven, properly implemented, and run.
• Assist in testing efforts and support requirements from Model Risk Management (2nd line of Defense), participate in full model development, validation and ongoing performance monitoring cycles

POSITION SPECIFICATIONS:

• Bachelor’s degree in a quantitative field such as Finance, Economics, Mathematics, Statistics, Computer Science, Engineering, or equivalent.
• Minimum of 3 years working with analytics, quantitative models (including governance responsibilities) or in model risk management.
• Experience in application and transaction fraud management in consumer lending or banking 
• Demonstrated Proficiency SQL, Python and or R
• Broad knowledge/understanding of both the consumer lending market and how analytics tools and techniques can drive business/fraud strategy
• Direct experience developing or validating complex analytical models that will be used for strategic decision making.
• Working knowledge of regulatory requirements and expectations for model risk management.
• Ability to understand, analyze and test complex models.
• Ability to work cross-functionally
• Strategic thinker with strong judgment and business sense; ability to influence at the highest levels of organizations
• Experience in a startup-like environment with expertise in designing and implementing data schemas will be a plus.
• Graduate degree in Statistics, Mathematics, Computer Science, Operations Research, Physics, Economics, Engineering, or a related technical field preferred.