At a Glance
- Tasks: Design and build AI-enabled automation tools for quantitative model lifecycle management.
- Company: Join Citi, a leading global bank with a focus on innovation.
- Benefits: Competitive salary, comprehensive health benefits, and opportunities for remote work.
- Other info: Collaborative environment with mentorship opportunities and career growth.
- Why this job: Make an impact in risk technology while working with cutting-edge AI and Python.
- Qualifications: STEM degree and strong Python skills required; financial services experience preferred.
The predicted salary is between 63000 - 77000 £ per year.
We are seeking a senior Python Developer within Risk Technology to join a multi-year strategic initiative: the design and delivery of AI-enabled automation across the end-to-end quantitative model lifecycle, covering all market risk and credit risk models.
This is a hands-on engineering role at the core of the program. You will design and build the tooling and services that power AI-assisted model documentation, automated model testing and validation workflows, large-scale risk data analysis, and model lifecycle management. You will work closely with quantitative analysts, model validators, data engineers, and the program leadership to translate workflow automation requirements into robust, production-grade solutions.
Key Responsibilities
- Design, develop, and maintain Python-based services, pipelines, and tools supporting automation of the quantitative model lifecycle across market risk and credit risk model families.
- Build and operate automated testing and validation frameworks for quantitative models, including test orchestration, result capture, benchmarking, and reporting.
- Develop data analysis and reconciliation tooling over large-scale risk datasets, ensuring data quality, lineage, and traceability across risk platforms.
- Contribute to model lifecycle management tooling: model inventory, workflow orchestration, approvals, periodic reviews, and audit-ready evidence generation.
- Implement AI/ML components within the model workflow, including LLM-based automation for model documentation generation and updating, intelligent data quality checks, and workflow assistance.
- Integrate AI tooling into a controlled, auditable, production-grade environment, with appropriate testing, monitoring, and governance controls.
- Stay current with developments in applied AI/ML and evaluate their applicability to risk technology use cases.
- Work within a cross-functional agile team alongside quants, validators, data engineers, and program management.
- Promote engineering best practices: code quality, testing, CI/CD, documentation, and secure, scalable design.
- Mentor junior developers and contribute to technical design reviews.
Required Qualifications
- STEM degree (Computer Science, Engineering, Mathematics, Statistics, Physics, or related); Master's degree preferred.
- Professional software development experience, with deep expertise in Python and its data/engineering ecosystem (e.g., pandas, NumPy, FastAPI, orchestration tools).
- Proven track record of delivering production-grade automation, data pipelines, or testing frameworks in a complex enterprise environment; financial services experience strongly preferred.
- Solid AI/ML knowledge, including practical experience with machine learning libraries and/or LLM-based application development (e.g., API integration, prompt engineering, RAG-style document workflows).
- Strong experience with test automation, CI/CD, and modern software engineering practices (Git, code review, containerization).
- Experience working with large datasets, data quality/linearity checks, and SQL; familiarity with enterprise data platforms.
- Ability to work effectively in a cross-functional, global team and communicate technical concepts to non-technical stakeholders.
Preferred Qualifications
- Exposure to quantitative risk models (market risk and/or credit risk) and the model lifecycle: development, validation, documentation, and ongoing monitoring.
- Familiarity with the model risk regulatory landscape and governance expectations in banking.
- Experience with workflow orchestration platforms, cloud environments (AWS/Google Cloud), and container orchestration (Docker/Kubernetes).
- Background in quantitative finance, statistics, or data science; an advanced quantitative degree is a plus.
- Experience mentoring engineers and leading small technical workstreams.
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.
Senior Python Developer - Quant Models AI Automation, Vice President in London employer: CitiGroup
Citi is an exceptional employer that offers a dynamic work environment where employees can thrive and make a significant impact in the investment banking sector. With a strong focus on professional development, team collaboration, and community engagement, associates are empowered to grow their careers while contributing to meaningful projects within the Consumer, Luxury & Retail team. Located in a vibrant city, Citi provides unique opportunities for networking and exposure to leading global consumer players, making it an ideal place for ambitious professionals seeking rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Python Developer - Quant Models AI Automation, Vice President in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at CitiGroup or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to CitiGroup.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like CitiGroup.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like CitiGroup that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior Python Developer - Quant Models AI Automation, Vice President in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at CitiGroup.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at CitiGroup and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at CitiGroup
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If CitiGroup uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
