Job DescriptionWe are seeking an experienced Quantitative Analyst (VP) to join our Markets Quantitative Analysis team in New York City. This is a senior role for an individual with deep expertise in RMBS securitized products and whole loans quantitative modeling. You will be responsible for driving the application of advanced analytics and machine learning within the securitized products business, as well as managing and mentoring junior quants. You will collaborate closely with the trading desk. You will be expected to generate impactful data analysis and trade ideas, build sophisticated models, and harness enormous datasets for in-depth analysis of RMBS/ABS securities. You will build and deploy models and analytics using C++, Python, and SQL, with a strong emphasis on leveraging AI and ML tools.
Responsibilities:- Lead the development, implementation, and validation of sophisticated models to price and assess risk on RMBS and ABS securities.
- Apply advanced statistical and ML modeling to project prepayment, default rates, and other credit-related metrics, and to identify complex, actionable patterns within large financial datasets
- Directly support trading desk and F&S business by developing data analysis tools and reports.
- Collaborate with other groups including risk management, technology, and the model validation group.
- Mentor, guide, and manage junior quants on the team, fostering their technical and professional growth.
Ideal Candidate:- 4-6 years of experience developing prepayment and default models for pricing and risk management for different mortgage types such as prime jumbo, Alt-A/Non-QM, RPL, CRT, etc.
- Significant experience working directly with trading and F&S desks and providing analytical support for various trading activities.
- Significant experience working with various mortgage databases such as LoanPerformance and Fannie/Freddie Credit Risk transfer, and the ability to develop data analysis tools and reports.
- Expertise with cashflow analytics tools such as Intex, Bloomberg and Yield Book.
- Significant, expert-level experience in programming including C++, SQL, and Python, machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
- Possesses excellent communication skills, with the ability to explain complex quantitative concepts to senior stakeholders.
Education- Graduate degree (Masters or PhD) in Computer Science, Mathematics, Physics, Engineering, or another quantitative field.
Other job-related duties may be assigned as required.
Job Family Group: Institutional Trading
Job Family:Quantitative Analysis
Time Type:Full time
Primary Location:New York New York United States
Primary Location Full Time Salary Range:$175,000.00 - $250,000.00
In addition to salary, Citi's offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.
Most Relevant Skills Please see the requirements listed above.
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.
Anticipated Posting Close Date:Jul 28, 2026
Automated Processing and AIWe use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
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