Hybrid VP Software Engineer – Risk Modeling & Data APIs

Citi; New York (NY); Hybrid; USD 79,000 - 114,000; Full time

Job summary

Citi is hiring a Software Engineer, Vice President to advance QRL (Quant Risk Libraries) with graph-based model-driven computations and robust infrastructure APIs. You will contribute to Python-based pipelines, data storage, and testing while collaborating with physicists, engineers and computer scientists to deliver scalable risk models.

The role emphasizes strong Python skills, experience with C/C++, and exposure to numerical libraries like Pandas/Numpy, aiming to enhance the risk modeling and

Qualifications

• Bachelor's/Master's/Ph.D. in CS/CE or related field.
• 3-5 years of professional Software Development experience.
• 2+ years developing Python, C or C++ packages and API development.
• Fluency in Python and working knowledge of a compiled language like C/C++/Java.
• Exposure to Pandas/Numpy and data processing.
• Ability to abstract and reason about program behavior from hardware to applications.

Responsibilities

• Designing and implement a framework for model driven computations on a graph.
• Designing and building infrastructure APIs for grid computing, data storage and access.
• Unit testing, reliability and improving the quality of our compute pipelines.
• Learn about Python, its ecosystem, community and best practices.
• Ideas on improving our model and data platform and help implement them.

Skills

Python

C/C++

Algorithms

Data structures

API development

Pandas/Numpy

Education

Bachelors, Masters or Ph.D. in Computer Science/Computer Engineering or related field

Tools

Flask

Django

Job description

Citi is hiring a Software Engineer, Vice President to advance QRL (Quant Risk Libraries) with graph-based model-driven computations and robust infrastructure APIs. You will contribute to Python-based pipelines, data storage, and testing while collaborating with physicists, engineers and computer scientists to deliver scalable risk models.

The role emphasizes strong Python skills, experience with C/C++, and exposure to numerical libraries like Pandas/Numpy, aiming to enhance the risk modeling and