6 days ago
Base Salary
$142k - $213k/yr
Responsibilities
- Design, develop, and maintain Python services, pipelines, and tools for automating quantitative model lifecycle workflows across market and credit risk models.
- Build automated testing and validation frameworks with test orchestration, result capture, benchmarking, and reporting.
- Develop risk-data analysis and reconciliation tooling with data quality, lineage, and traceability controls.
- Build model inventory, workflow orchestration, approval, periodic-review, and audit-evidence tooling.
- Implement LLM-based documentation automation, intelligent data-quality checks, and workflow-assistance capabilities in controlled production environments.
- Apply testing, monitoring, governance, secure design, and scalable engineering practices to AI-enabled tooling.
- Collaborate with quants, validators, data engineers, and program leadership, mentor junior developers, and contribute to technical design reviews.
Requirements
- 7+ years of professional software development experience with deep Python and data/engineering ecosystem expertise.
- Production experience delivering automation, data pipelines, or testing frameworks in complex enterprise environments; financial services experience is strongly preferred.
- Practical AI/ML experience, including machine learning libraries or LLM application development such as API integration, prompt engineering, or RAG-style document workflows.
- Strong experience with test automation, Git, code review, containerization, and modern software engineering practices.
- Experience with large datasets, data-quality and lineage checks, SQL, and enterprise data platforms.
- Ability to collaborate globally and communicate technical concepts to non-technical stakeholders.
- Exposure to quantitative market or credit risk models and their development, validation, documentation, and monitoring lifecycle is preferred.
- Familiarity with banking model-risk regulation and governance, workflow orchestration platforms, AWS or Google Cloud, and Docker or Kubernetes is preferred.
- Background in quantitative finance, statistics, or data science and experience mentoring engineers or leading technical workstreams are preferred.
- A STEM degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field is required; a Master's degree is preferred.
Benefits
- Annual base salary range of $142,320.00-$213,480.00.
- Medical, dental, and vision coverage; 401(k); life, accident, and disability insurance; and wellness programs.
- Paid vacation, sick leave, and holidays.
- Full-time role based in New York, New York, United States.
Categories
About Citi
Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients. We have over 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. We are Citi, the global bank – an institution connecting millions of people across hundreds of countries and cities. For information on Citi’s commitment to privacy, visit on.citi/privacy.