Quant Modeling Associate - Credit Risk & Validation

JPMorgan Chase & Co.

City of Rochester (NY)

On-site

USD 120,000 - 190,000

Full time

25 hours ago
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Benefits offered by this job

Health care
Retirement plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching

Job summary

JPMorgan Chase & Co. in New York City is seeking a Quant Modeling Associate in the MRGR team to cover counterparty credit risk models across asset classes. You will interact daily with quantitative research, credit risk, and trading desks to ensure sound methodologies and robust governance.

The role emphasizes reviewing methodologies, testing adequacy, and clear communication of model risks. A master’s degree in a quantitative field and strong programming skills are required, with collaboration

Qualifications

  • Master’s degree in mathematics, statistics, or related field.
  • Strong quantitative, analytical, and problem-solving skills.
  • Experience in banking analytics or similar environment.
  • Ability to work independently and meet deadlines.
  • Strong communication and teamwork.
  • Inquisitive and able to assess materiality.

Responsibilities

  • Review margining methodologies and credit risk measurement.
  • Evaluate model soundness, inputs, assumptions, and limitations.
  • Assess testing adequacy and correctness of implementation.
  • Assist with model governance, issues, and performance monitoring.
  • Collaborate with model developers, credit risk officers, and traders.

Skills

Mathematics
Statistics
Quantitative Finance
Problem solving
Independent work
Communication
Python
R
Model validation

Education

Master's degree in Mathematics/Statistics/Engineering/Quantitative Finance

Tools

Python
R
SAS

Job description

JPMorgan Chase & Co. in New York City is seeking a Quant Modeling Associate in the MRGR team to cover counterparty credit risk models across asset classes. You will interact daily with quantitative research, credit risk, and trading desks to ensure sound methodologies and robust governance.

The role emphasizes reviewing methodologies, testing adequacy, and clear communication of model risks. A master’s degree in a quantitative field and strong programming skills are required, with collaboration

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