Quantitative Modeling Lead [Multiple Positions Available]

Duties: Design and monitor model performance metrics. Review and build benchmark model for retail credit risk related models. Assess and help mitigate the model risk of complex models used in the context of credit card scorecard models for decision-making purposes. Validate models by evaluating conceptual soundness. Design and conduct experiments to compare a models prediction against actual outcomes or against the output of alternative benchmark models. Own validation projects including planning execution coordination and final delivery. Drive all phases of the model review process while also contributing individual technical assessments. Conduct validation of regulatory models related to capital stress testing. Drive coordination of the Annual Status Assessment (ASA) process for the Consumer and Community Banking line of business. Conduct no-change re-reviews and minor model enhancement reviews.

QUALIFICATIONS:

Minimum education and experience required: Ph.D. in Aeronautics and Astronautics Engineering (any) Statistics Computer Science Mathematics or related field of study plus one (1) year of experience in the job offered or as Quantitative Modeling Lead Research Assistant or related occupation. The employer will alternatively accept a Masters in Aeronautics and Astronautics Engineering (any) Statistics Computer Science Mathematics or related field of study plus three (3) years of experience in the job offered or as Quantitative Modeling Lead Research Assistant or related occupation.

Skills Required: This position requires experience with the following: conducting model development risk management underwriting or portfolio performance analysis for credit card portfolios mortgage products or auto services loans within the financial services industry; building validating and interpreting logistic regression and Linear Regressions models using real-world data that is collected from actual events processes or observations in daily situations rather than generated from idealized simulated environments; assessing projects where models were used for classification and regression tasks evaluating the models metrics and assessing how the results were applied to drive business decisions; implementing machine learning solutions end-to-end including data preprocessing algorithm selection model training and deployment in a production or research setting; time series modeling including trend seasonality and forecasting analyses; programming in R or Python to perform data analysis model development or automation of analytical processes; formulating hypotheses selecting modeling techniques back-testing predictions and documenting performance metrics to ensure robustness and regulatory compliance; applying Xgboost to improve model predictive performance; applying hyperparameter optimization techniques and applying explainability methods to assess feature importance including using Shapley values for model interpretability; applying ensemble methods such as Random Forest for classification or regression.

We offer a competitive total rewards package including base salary determined based on the role experience skill set and location. For those in eligible roles discretionary incentive compensation which may be awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs based on eligibility. These benefits include comprehensive health care coverage on-site health and wellness centers a retirement savings plan backup childcare tuition reimbursement mental health support financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring addition please visit: Location: 545 Washington Blvd Jersey City NJ 07310.

Full-Time. Salary: $164000 - $215000 per year.