Stress-Testing Quantitative Analyst (SAS/Python)

Jobtailor; New Jersey; On-site; USD 85,000 - 120,000; Full time

Job summary

TD Bank is seeking an experienced quantitative analyst to join the treasury model development team in New Jersey. You will help forecast balance and fee income across loan and deposit products, developing advanced models for pricing and risk assessment.

The role requires strong SQL, SAS, Python, and R skills, with the ability to interpret results, communicate clearly, and present findings to stakeholders. A quantitative background and effective collaboration are essential.

Qualifications

• Undergraduate degree in a quantitative field; advanced degree preferred.
• Strong knowledge of quantitative models and statistical analysis.
• 0 to 1 year of experience in developing quantitative models; CCAR/PPNR/DFAST experience a plus.
• Strong hands-on expertise with SQL, SAS, Python, and R.
• Proficient communication and ability to present analysis results.

Responsibilities

• Support treasury model development team in forecasting balance and fee income.
• Provide specialized quantitative analytical and modeling support.
• Develop advanced quantitative models for product pricing.
• Conduct complex quantitative analyses for areas of responsibility.
• Perform tests of model assumptions for soundness.
• Review model results and identify unexpected results.
• Develop conclusions and actions to rectify discrepancies and analyses.
• Develop and analyze key metrics and variances.

Skills

SQL

SAS

Python

R

Education

Undergraduate degree

Advanced degree preferred

Tools

Microsoft Office

Job description

TD Bank is seeking an experienced quantitative analyst to join the treasury model development team in New Jersey. You will help forecast balance and fee income across loan and deposit products, developing advanced models for pricing and risk assessment.

The role requires strong SQL, SAS, Python, and R skills, with the ability to interpret results, communicate clearly, and present findings to stakeholders. A quantitative background and effective collaboration are essential.