Model Validation Role - Bank

Role -Individual Contributor

- 5-8 years of experience with minimum Masters/Phd in a quantitative field such as applied math, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis

- Deep understanding of Regression (OLS, Logistic, Time series, Machine Learning Algorithm )

- Detail knowledge of Banking Regulations and guidelines

- Performing model validations and clearly documenting evidence of validation activities

- Develop benchmarking and alternative models in Python/R/Matlab/SAS

- Providing effective challenge to models developed in/for the lines of business, including identifying conceptual weaknesses in a model and understanding tradeoffs with other approaches

- Managing and mitigating model risk to meet or exceed regulatory and industry standards

- Providing leadership and consultation to less experienced validators and business partners

- Communicating model risk findings and limitations to key stakeholders

- Contributing to the improvement of model building and model use practices

- Providing analytical support and offering insights regarding a wide array of business initiatives

- Interacting with senior management and regulators on key modeling issues, including the identification, management, and mitigation of model risk

- Proactively following the industry trend to apply and develop new technology to improve efficiency

Desired Skills :

- Strong mathematical, statistical, analytical and computational skills

- Strong communication skills for a variety of audiences (other technical staff, senior management and regulators) both verbally and in writing

- Capability to multi-task and finish work within strict timelines and provide timely requests for information and follow-up questions

- Ability to work independently on complex model validations from start to finish

- Able to demonstrate first-hand knowledge of advanced topics in various mathematical and numerical methods such as Monte Carlo, stochastic calculus, differential equations, linear algebra, applied probability, and statistics

- Skill in managing relationships with key model stakeholders

- Eagerness to contribute collaboratively on projects and discussions

- Perpetual interest in learning something new, but being comfortable with not knowing the all the answers

- Attention to detail in both analytics and documentation

- Aptitude for synthesizing data to 'form a story' and align information to contrast/compare to industry perspective

- Intellectually curious, who enjoy solving problems.