- Develop models, using C++, Python, and SQL, to price and assess risk on CMBS securities.
- Writing complex queries and build analytics to analyze enormous CMBS dataset and provide analysis, reports, and historical performance trends.
- Helping develop web applications that will allow traders to access the underlying mortgage data to perform different types of analysis and to run the models/analysis on CMBS securities.
- Reviewing, verifying, and maintaining highest quality of indicative data that feeds the models and web applications that trading business heavily rely on.
- Work with various other groups including internal risk management group, technology team, model validation group, and clients for both day-to-day issues such as running risk reports, providing data and analysis, addressing incorrect model projections and data issues, as well as longer term projects.
- Monitor CMBS market activity and provide traders with updated market news and potential impact on collateral performance and market pricing. Emphasis will also be on trade idea generation and sector specific research.
- Contributing as part of a team in providing innovative ideas and input that are expected and sought from everyone involved.
- Ideal Candidate:
- Graduate degree in Computer Science, Mathematics, or any Quantitative field of study.
- Strong programming skills preferably in C++ and Python.
- 5+ years of experience in CMBS, with proven knowledge of the product area.
- Experience working with large datasets and having exposure to commercial mortgage databases such as Trepp, CoStar, and Intex.
- Experience with industry standard tools such as Intex, Bloomberg, and Trepp.
- High attention to detail.
- Possesses good communication skills
- Bachelors/University degree, Masters degree preferred
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Description
We are looking for a Quantitative Analyst to join the Markets Quantitative Analysis team in New York City. The team is primarily responsible for providing data analysis, developing quantitative models for projecting prepayment and default rates, and developing related analytics to assist trading and risk management of the securitized sectors including agency/non-agency RMBS, CMBS, and ABS. The specific role will focus on supporting the CMBS and CRE trading desk and F&S business.
As a Quantitative Analyst there is a huge opportunity to learn within this role as you will be working with senior analysts and trading desks helping them develop and improve complex models, provide data analysis and trade ideas, and develop analytics to access enormous dataset to enable in-depth analysis of CMBS securities.
In this quantitative role, you will build models and analytics using C++, Python, and SQL. The Analyst will be an integral part of the trading process, where the emphasis will be on delivering intuitive models, analytics that allow in-depth data analysis of underlying loans, and providing an insightful value-added service for the trading business by generating analysis that leads to trade recommendation or identifying mispriced securities. The successful Analyst will effectively balance daily functions with numerous ad-hoc requests.
Responsibilities:
Education:
This job description provides a high-level review of the types of work performed. 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:
$200, $300,000.00In addition to salary, Citis 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 Available offerings may vary by jurisdiction, job level, and date of hire.
Anticipated Posting Close Date:
May 22, 2024
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