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Credit Model Development

Remote:

Full Remote

Contract:

Full time

Experience:

Senior (5-10 years)

Work from:

North Carolina (USA), United States

Offer summary

Qualifications:

Bachelor's or Master's in a quantitative discipline, 5+ years experience in Risk or Finance without degree, 3+ years in Consumer Lending statistical modeling/analytics, 2+ years coding with Python or PySpark.

Key responsabilities:

Develop and maintain loss forecasting and capital models
Analyze client-level data and identify trends in sales/payment behavior

LanceSoft, Inc. XLarge https://www.lancesoft.com

5001 - 10000 Employees

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Job description

Develop, implement, and maintain an integrated loss forecasting and capital modeling suite that supports overall alignment between baseline and stressed scenarios, as well as capital planning initiatives using PySpark/Python/SAS or other programing language and big data
Support the development of balance and revenue forecasting models, encompassing data, statistics, modeling and business acumen
Extract and analyze client level data using structured and/or unstructured data across several data warehouses to generate actionable insights and inputs to model development
Analyze data to identify patterns and trends across sales/payment/delinquency behavior
Adapt automation and develop alternative predictive methodologies (Machine Learning) and/or cloud initiatives (AWS) to current and future models to enhance functionality
Plan and execute self-driven analytics using next generation technologies, prepare analysis and reports to support discussions on key analytics and model aspects to drive decision making
Manipulate large data sets and use them to identify trends and reach meaningful conclusions to inform strategic business decisions
Develop attribution analysis and synthesize results to evaluate the applicability of existing models for cross-functional use, identify gaps and develop solutions to reduce process redundancies
Familiarity with Model Governance trends/developments across the banking sector, especially as related to credit card or consumer lending (SR11-7)
Strong communication skills to facilitate complex discussions in productive and collaborative manner
Develop alternative predictive methodologies/ tools to better identify credit dynamics in portfolio performance

Qualifications/Requirements:

Bachelors or Masters in Mathematics/Statistics, Computer Science, Economics, Finance or other quantitative discipline; or in lieu of a degree 5+ years’ experience in Risk, Finance, Consumer Lending
3+ years of experience in Consumer Lending statistical modeling/analytics, preferably related to CECL and/or Loss Forecasting modeling for credit cards
2+ years in coding with Python, PySpark or other equivalent language within the past 5 years
Detailed-oriented, high level of intellectual curiosity and strong sense of ownership
Good business acumen and the ability to connect data with business decisions
Experience in developing statistical loss forecasting models, PD/ EAD modeling desired.

Must Have:

Detailed-oriented, high level of intellectual curiosity and strong sense of ownership.
Experience in developing statistical loss forecasting models, PD/ EAD modeling desired