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Quant Modeling Lead [Multiple Positions Available]

at J.P. Morgan

Back to all Data Science / AI / ML jobs
J.P. Morgan logo
Bulge Bracket Investment Banks

Quant Modeling Lead [Multiple Positions Available]

at J.P. Morgan

Mid LevelNo visa sponsorshipData Science/AI/ML

Posted 6 days ago

No clicks

Compensation
$163,300 – $215,000 USD

Currency: $ (USD)

City
Not specified
Country
United States

Lead design and develop independent benchmark models for credit risk, including dataset preparation, model design, and performance testing. Responsible for validating credit risk models using machine learning with explainability to ensure regulatory compliance and Basel CECL/CCAR alignment. Coordinate governance, monitoring, and documentation, support regulatory examinations, and communicate model limitations and strengths to senior management.

Location: Jersey City, NJ, United States

DESCRIPTION:

Duties: Design and develop independent benchmark models for credit card models, including dataset preparation, model design, performance testing. Conduct comprehensive assessments on the benchmark credit model used for loss forecasting to ensure the robustness and reliability of the champion credit model. Conduct model validation on credit risk models that utilize machine learning techniques with explainability to ensure compliance with regulatory policy. Provide guidance on a model's appropriate usage and ensure that model users are aware of model strengths and limitation. Validate capital models and ensure they are compliant with Basel regulatory policy, including default definitions, methodology, and quantification criteria. Work with model developers to establish action plans and corresponding timelines for model risk issues. Conduct testing of LLM prompt engineering to facilitate automating certain governance processes. Assist with regulatory examinations, by working with internal team to deliver precise and accurate responses to inquiries. Assess qualitative adjustments to capture risks not reflected in the model output to comply with CECL policy. Review qualitative model (QM) requested by regulators by evaluating business assumption and quantitative techniques. Organize quarterly exit meetings and present a summary of the ongoing monitoring plan for credit risk models to senior management team. Coordinate governance activities, including performance monitoring and annual assessments, by collaborating with product teams and managing processes and deadlines. Oversee the management of model risk issues and limitations for credit risk models, ensuring they are accurately documented on the platform. Collaborate with the modeling team to design Ongoing Performance Monitoring (OPM) and Early Warning Analysis (EWA) for model performance in production. Collaborate with the teams to complete model review documentation, including evaluation of key elements of model risk, assessment of estimation diagnostics, assessment of implementation testing, outcome analysis, and ongoing performance monitoring.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Quantitative and Computational Finance, Statistics, Data Analytics, Mathematics, or related quantitative field of study plus three (3) years of experience in the job offered or as Quant Modeling Lead, Quantitative Modeling/Management Associate, Model Risk Associate, or related occupation.

Skills Required: This position requires three (3) years of experience with the following skills: performing data manipulation, data structuring, and data design flow and query optimization using Python, R, and SQL programming languages; conducting benchmarking and statistical analysis using fundamental statistical learning algorithms, including linear regression, logistic regression, and clustering; optimizing XgBoost models via hyperparameter tuning; assessing XgBoost model performance using feature importance analysis and Shapley value computations; and developing and validating credit risk models (including default models for CCAR and CECL) tailored for credit card, mortgage, or auto loan retail products.

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 process. In addition, please visit: https://careers.jpmorgan.com/us/en/about-us.

Job Location: 545 Washington Boulevard, Jersey City, NJ 07310

Full-Time. Salary:  $163,300 - $215,000 per year.

Design and develop independent benchmark models for credit card models, including dataset preparation, model design...

Quant Modeling Lead [Multiple Positions Available]

at J.P. Morgan

Back to all Data Science / AI / ML jobs
J.P. Morgan logo
Bulge Bracket Investment Banks

Quant Modeling Lead [Multiple Positions Available]

at J.P. Morgan

Mid LevelNo visa sponsorshipData Science/AI/ML

Posted 6 days ago

No clicks

Compensation
$163,300 – $215,000 USD

Currency: $ (USD)

City
Not specified
Country
United States

Lead design and develop independent benchmark models for credit risk, including dataset preparation, model design, and performance testing. Responsible for validating credit risk models using machine learning with explainability to ensure regulatory compliance and Basel CECL/CCAR alignment. Coordinate governance, monitoring, and documentation, support regulatory examinations, and communicate model limitations and strengths to senior management.

Location: Jersey City, NJ, United States

DESCRIPTION:

Duties: Design and develop independent benchmark models for credit card models, including dataset preparation, model design, performance testing. Conduct comprehensive assessments on the benchmark credit model used for loss forecasting to ensure the robustness and reliability of the champion credit model. Conduct model validation on credit risk models that utilize machine learning techniques with explainability to ensure compliance with regulatory policy. Provide guidance on a model's appropriate usage and ensure that model users are aware of model strengths and limitation. Validate capital models and ensure they are compliant with Basel regulatory policy, including default definitions, methodology, and quantification criteria. Work with model developers to establish action plans and corresponding timelines for model risk issues. Conduct testing of LLM prompt engineering to facilitate automating certain governance processes. Assist with regulatory examinations, by working with internal team to deliver precise and accurate responses to inquiries. Assess qualitative adjustments to capture risks not reflected in the model output to comply with CECL policy. Review qualitative model (QM) requested by regulators by evaluating business assumption and quantitative techniques. Organize quarterly exit meetings and present a summary of the ongoing monitoring plan for credit risk models to senior management team. Coordinate governance activities, including performance monitoring and annual assessments, by collaborating with product teams and managing processes and deadlines. Oversee the management of model risk issues and limitations for credit risk models, ensuring they are accurately documented on the platform. Collaborate with the modeling team to design Ongoing Performance Monitoring (OPM) and Early Warning Analysis (EWA) for model performance in production. Collaborate with the teams to complete model review documentation, including evaluation of key elements of model risk, assessment of estimation diagnostics, assessment of implementation testing, outcome analysis, and ongoing performance monitoring.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Quantitative and Computational Finance, Statistics, Data Analytics, Mathematics, or related quantitative field of study plus three (3) years of experience in the job offered or as Quant Modeling Lead, Quantitative Modeling/Management Associate, Model Risk Associate, or related occupation.

Skills Required: This position requires three (3) years of experience with the following skills: performing data manipulation, data structuring, and data design flow and query optimization using Python, R, and SQL programming languages; conducting benchmarking and statistical analysis using fundamental statistical learning algorithms, including linear regression, logistic regression, and clustering; optimizing XgBoost models via hyperparameter tuning; assessing XgBoost model performance using feature importance analysis and Shapley value computations; and developing and validating credit risk models (including default models for CCAR and CECL) tailored for credit card, mortgage, or auto loan retail products.

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 process. In addition, please visit: https://careers.jpmorgan.com/us/en/about-us.

Job Location: 545 Washington Boulevard, Jersey City, NJ 07310

Full-Time. Salary:  $163,300 - $215,000 per year.

Design and develop independent benchmark models for credit card models, including dataset preparation, model design...

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