Consultant Model Validation
Consultant Model Validation
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Job Description
About Northern Trust:
Northern Trust a Fortune 500 company is a globally recognized awardwinning financial institution that has been in continuous operation since 1889.
Northern Trust is proud to provide innovative financial services and guidance to the worlds most successful individuals families and institutions by remaining true to our enduring principles of service expertise and integrity. With more than 130 years of financial experience and over 22000 partners we serve the worlds most sophisticated clients using leading technology and exceptional service.
Summary:
The Model Risk Management Group (MRMG) is a centralized model risk management function within the Bank. It has seen fast growth in the past few years reflecting global regulators increasing attention on model risk. We are searching for an Consultant Risk analytics to join our team. The primary responsibility of this role is to support the model validation function. Responsible for acting as a lead contributor in the discovery and diagnostic of model related risks including input data assumption conceptual soundness methodology outcomes analysis benchmarking monitoring and model implementation.
Specific Responsibilities
Validates models that are typically developed in Python or SAS. Able to challenge conceptual soundness of machine learning models as well as assure that appropriate and good quality data was used for development.
Has advanced proficiency of financial models used in portfolio analysis asset management Value at Risk Monte Carlo CAPM Factors.
Has solid understanding of risks that are posed by AI/ML models (Fairness Privacy Transparency and Explainability etc.
Has good understanding of stress testing CCAR CECL etc.
Solves complex quantitative problems and takes a new perspective on existing solutions.
Analyzes possible solutions using technical experience and judgment and precedents.
Develops and maintains an understanding of many algorithms across supervised learning unsupervised learning and time series analysis.
Utilizes expertise in machine learning algorithms and statistics to challenge how algorithms are selected trained and tested.
Perform reviews of bankwide quantitative models including models used for CECL and CCAR/DFAST stress testing credit risk loss projections (PD LGD EAD) operational risk interest rate risk models AML (AntiMoney Laundering and Fraud Detection) and various machine learning models.
Ensure model development monitoring and validation approaches meet regulatory expectations such as SR 117 and internal risk management needs.
Evaluate conceptual soundness of model specifications; reasonableness of assumptions and reliability of inputs; completeness of testing performed to support the correctness of the implementation; robustness of numerical aspects; suitability and comprehensiveness of performance metrics and risk measures associated with model use.
Review model documents and conduct test runs on model codes.
Assess and measure the potential impact of model limitations parameter estimation error and/or deviations from model assumptions; compare model outputs with empirical evidence and/or outputs from model benchmarks.
Document and present observations to Model Validation Team Lead and to model owners and users recommend remediation action plans track remediation progress and evaluate remediation evidence.
Monitor model performance reports on an ongoing basis to ensure models remain valid as well as contribute in the bankwide model risk and control assessment.
Support development of comprehensive documentation and testing of risk management framework. Deliver a work product that requires little revision.
Establish and maintain strong relationship with key functional stakeholders such as model developers model owners and users.
Qualifications
6 to 8 years of modeling or quantitative analysis experience preferably in a discipline relevant to risk management to include statistical/mathematical and financial modeling.
A College or University degree in STEM field mathematics actuarial science engineering or statistics or related discipline (Advanced degree preferred).
Good interpersonal verbal and written communication skills.
Programming experience in Python required experience in SAS and R desired.
Mastery of analytical tools such as Excel as well as Word and PowerPoint is required.
Deep understanding of linear regression and logistic regression.
Experience with Machine Learning models (supervised/unsupervised learning neural networks classification clustering hyperparameter tuning etc. desired.
Familiarity with cloud and big data technologies is desired.
Working with Us:
As a Northern Trust partner greater achievements await. You will be part of a flexible and collaborative work culture in an organization where financial strength and stability is an asset that emboldens us to explore new ideas.
Movement within the organization is encouraged senior leaders are accessible and you can take pride in working for a company committed to assisting the communities we serve! Join a workplace with a greater purpose.
Wed love to learn more about how your interests and experience could be a fit with one of the worlds most admired and sustainable companies! Build your career with us and apply today. #MadeForGreater
Reasonable accommodation
Northern Trust is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation for any part of the employment process please email our HR Service Center at .
We hope youre excited about the role and the opportunity to work with us. We value an inclusive workplace and understand flexibility means different things to different people.
Apply today and talk to us about your flexible working requirements and together we can achieve greater.
Required Experience:
Contract
Employment Type
Full-Time
