Job Description

This role will contribute to the development and maintenance of cutting-edge risk modeling systems. You will work with a team of talented engineers and quantitative analysts to build and deploy robust and scalable solutions for complex risk challenges.

Key Responsibilities:

• Design and implement a framework for model-driven computations on a graph-based architecture.
• Develop and maintain infrastructure APIs for grid computing, data storage, and access.
• Conduct unit testing, ensure reliability, and continuously improve the quality of compute pipelines.
• Proactively learn and apply best practices within the Python ecosystem.
• Contribute innovative ideas to enhance the model and data platform and assist in their implementation.

Qualifications:

Required:

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field.
• Strong foundation in computer science fundamentals: data structures, algorithms, operating systems, and programming languages.
• Proficiency in Python and working knowledge of a compiled language (C/C++/Java).
• Experience with numerical libraries (Pandas/NumPy) and data processing techniques.
• 2+ years of experience developing Python, C, or C++ packages and APIs.
• Excellent analytical and problem-solving skills with the ability to think abstractly and reason about program behavior at different levels.

Preferred:

• Experience with web services and frameworks like Flask or Django.
• Experience with large-scale scientific computing and algorithm development.
• Strong interest in finance and financial markets (experience is a plus).
• Experience contributing to open-source projects.

About the Role:

This position offers a unique opportunity to work on impactful projects at the intersection of finance, technology, and quantitative analysis. You will gain valuable experience in building and deploying sophisticated risk models while collaborating with a team of highly skilled professionals.