VP, AI-Driven Risk Modeling & Python Automation

Citigroup Inc.

Greater London

On-site

GBP 90,000 - 130,000

Full time

3 days ago
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Job summary

Citi seeks a senior Python Developer in Risk Technology to design and deliver AI-enabled automation across the end-to-end quantitative model lifecycle, covering market risk and credit risk models. This hands-on engineering role builds tooling and services powering model documentation, automated testing, and data analysis.

You will collaborate with quants, validators, data engineers, and leadership, promote engineering best practices, and mentor junior developers while ensuring production-grade,

Qualifications

  • Requires a STEM degree with strong Python and data/engineering experience.
  • Proven track record delivering production-grade automation in a complex enterprise environment.
  • Experience with data pipelines, testing frameworks, and model lifecycle tooling.
  • Solid AI/ML knowledge and practical API integration or prompt engineering.

Responsibilities

  • Design, develop, and maintain Python-based services, pipelines, and tools for automated model lifecycle tasks.
  • Build and operate testing and validation frameworks for quantitative models.
  • Develop data analysis and reconciliation tooling over large risk datasets.
  • Contribute to model lifecycle tooling, including approvals, reviews, and auditable evidence generation.

Skills

Python programming
Cross-functional collaboration
Mentoring

Education

STEM degree (CS/Engineering/Math/Statistics/Physics)
Master's degree preferred

Tools

Pandas
NumPy
FastAPI
Git
CI/CD
Docker
Kubernetes
SQL
Orchestration tools
LLM-based development

Job description

Citi seeks a senior Python Developer in Risk Technology to design and deliver AI-enabled automation across the end-to-end quantitative model lifecycle, covering market risk and credit risk models. This hands-on engineering role builds tooling and services powering model documentation, automated testing, and data analysis.

You will collaborate with quants, validators, data engineers, and leadership, promote engineering best practices, and mentor junior developers while ensuring production-grade,

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