Lead Model Implementation

In this role, you will :

Lead complex, large-scale model maintenance, optimization, and planning initiatives related to operational processes, controls, reporting, testing, implementation, and documentation

Review and analyze complex multi-faceted model operations and optimization challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors

Develop model processes and optimization strategies for short- and long-term objectives; support and provide insights regarding a wide array of business initiatives

Make decisions in complex and multi-faceted situations requiring solid understanding of agile development

Influence global assessment of model maintenance schedules inclusive of engineering, structure, and scope of review following the System Development Life Cycle process, quality, security, and compliance requirements

Strategically collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals

Desired Qualifications :

Overall experience of 5-14 years in Risk Analytics

Degree in applied mathematics, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business / social and behavioral sciences with a quantitative emphasis.

Strong Quantitative Skills :

5+ years of Predictive modeling experience. Good understanding of model development and model testing.

Proficient in statistical analysis

Good Problem Solving and Analytical Skills

Programming Skills

2+ years of hand- on experience in Python and SQL

1+ years of experience in SAS

Good Written and Oral Communication Skills

Ability to prioritize work, meet deadlines, achieve goals and work under pressure in a dynamic and complex environment

Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities

Understanding of bank regulatory data sets and other industry data sources

Ability to research and report on a variety of issues using problem solving skills

Ability to make timely and independent judgment decisions while working in a fast-paced and results-driven environment

Job Expectations :

Lead and perform various complex activities related to model implementation, production and model analytics. Provide analytical support for developing, evaluating, implementing, monitoring and executing credit and PPNR models across commercial business vertical

Development of regulatory Credit risk (including CCAR, CECL and IFRS), RRP Valuation, and PPNR models for Commercial portfolio in SAS / Python.

Lead complex model development projects independently and support multiple priorities

Migration of existing development / implementation codes from SAS to Python with thorough testing and UAT

Work closely with team to understand and enhance the data and modeling process behind existing models, develop new models, address data and model issues / findings.

Underlying portfolio data research and analytics using strong programming skills

Adhere to audit and model validation governance to ensure data and modeling process are in compliance with policy and are working as intended, address model validation and regulatory feedback issues