Role Overview:
Citi is seeking an experienced Quantitative Model Developer with a strong background in model implementation and Python programming. This role is critical for designing and implementing interconnected quantitative models used across risk management. The ideal candidate will have experience working in financial services and possess advanced technical, analytical, and communication skills.
Key Responsibilities:
- Lead and standardize model implementation best practices.
- Build reusable code components such as libraries, functions, and classes for model integration.
- Implement interconnected quantitative models on IT platforms.
- Act as a subject matter expert for junior developers and ensure quality, consistency, and documentation in model code.
Required Skills & Experience:
- 7+ years of professional experience with a Master's degree, or 5+ years with a Ph.D.
- Hands-on experience in quantitative model development and implementation, especially with logistic regression, OLS, and time series models.
- Strong Python programming skills must have a track record of developing standardized, efficient, and well-documented code.
- Experience implementing interconnected models where outputs feed into other models.
- Exposure to macroeconomic forecasting (e.g., GDP projections).
- Background in financial services is required.
- Strong communication skills are essential.
Educational Requirements:
- Master's degree in a quantitative field (e.g., Mathematics, Statistics, Economics, Finance, Computer Science) is required.
- Ph.D. is preferred but not mandatory.
Resume Guidelines (Strict Compliance Required):
- Clearly state employment type and history (e.g., full-time, contract).
- No bold text or formatting errors; resumes with such issues will be automatically rejected.
- Lengthy or unfocused resumes are discouraged concise and well-organized resumes are preferred.
- Excellent written communication is a must.