Quantitative Software Developer
2 days ago
We are committed to developing state-of-the-art models and technology, driving our investment and risk management decision-making processes. This platform is driven by cutting-edge, cloud-based data & ML solutions.
Job OverviewThis is a hybrid credit modeling / software development role that requires estimating, developing, and enhancing credit models in the securitized products space via data-driven credit risk analysis.
Responsibilities:- Develop production-quality ETL and data integrity processes to build and maintain credit models.
- Create visual tools for monitoring, back-testing, and adjusting model performance.
- Collaborate with data scientists, analysts, traders, and other stakeholders to understand requirements and deliver high-quality data solutions.
As a Quantitative Software Developer - Structured Credit Specialist, you will play a key role in driving our investment and risk management decision-making processes.
Requirements:- BS in Computer Science, Statistics/Data Science, Mathematics, or Financial Engineering degree from a top university. MS degree preferred.
- 2-4 years' experience as a research modeler / quant developer in a hedge fund, asset manager, banking, or fintech environment focused on structured products or consumer credit.
- Proven modeling skills in R and Python. Experience building loan-level credit / prepayment models through all stages from data preparation, data analysis, model estimation through deployment into production.
- Experience with generalized regression models as well as machine learning frameworks.
- Very strong programming and software design skills (Python, C++) required.
- Excellent communication skills and ability to work collaboratively in a team environment with a flexible, organized, and driven personality.
- Knowledge of structured products and/or risk management in a fixed-income environment is required.
- Competitive salary and benefits package: $120,000 - $180,000 per year.
- A dynamic and inclusive work environment with opportunities for professional growth.
- Access to the latest technologies and tools in the data engineering field.
- Support for continuous learning and career development.
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