VP, Quant Developer - Risk Analytics
At a glance
VP-level Data Science role at Jefferies. New York · full-time · $175,000–$200,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build agent workflows that plan, carry out several steps and use tools for risk analysis and regulatory filings
- Take charge of AI risk platform design, from data movement and tool connections to orchestration and production launch
- Create tests that check AI-produced code and analytical results for accuracy in financial risk work
- Build command-line AI developer tools and code creation or review pipelines for risk analytics
- Work with Market Risk, Credit Risk and RegIM teams to turn requirements into Python solutions, libraries and reporting flows
What you bring
- At least five years developing Python backends for financial applications
- You have designed multi-step agent workflows and built professional checks for AI-generated results
- You have used LLM developer tools, including command-line agents or assisted code creation and review
- You can lead agent platform architecture and understand Market Risk and Credit Risk
- You have built reusable Python libraries; a quantitative master's is preferred, while a bachelor's may qualify with exceptional experience
Who this fits
This VP role suits a senior Python developer with financial risk expertise and hands-on experience building agentic systems. You’ll work with Market Risk, Credit Risk and RegIM teams on risk analytics and regulatory submissions.
From the employer
The Global Risk Analytics team is looking for a seasoned Quantitative Risk Developer to join our Quant Risk Development team. This role offers the opportunity to work closely with other risk analytics teams, including Market Risk, Credit Risk, and RegIM, to design and operate AI-powered systems that automate complex risk workflows and support regulatory submissions. The ideal candidate brings equal depth in Agentic Coding and financial risk domain knowledge, with hands-on experience structuring agentic workflows, validating AI-generated output, and architecting end-to-end systems in environments similar to Claude Code.
Key Responsibilities
- Design and implement end-to-end agentic workflows that enable autonomous planning, multi-step execution, and tool use across risk analytics and regulatory submission processes.
- Architect and own the full system design of AI-powered risk platforms, including data flow, tool integration, orchestration layer, and production deployment.
- Build and maintain validation frameworks and testing pipelines to ensure the correctness and reliability of AI-generated code and analytical outputs in a financial risk context.
- Develop and integrate LLM-powered developer tooling - including CLI-based agents and code generation/review pipelines - to accelerate risk analytics delivery.
- Collaborate with Market Risk, Credit Risk, and RegIM teams to translate complex domain requirements into robust, automated Python solutions.
- Develop scalable, reusable Python libraries and contribute to a robust CI/CD environment through testing, peer review, and version control.
- Facilitate efficient data processing, integration, and reporting pipelines to streamline regulatory submissions and internal analytics.
Required Qualifications
- Education: Master's degree in Financial Engineering, Mathematics, Computer Science, or a related quantitative field preferred; Bachelor's considered with exceptional experience.
- Experience: At least 5 years of professional experience in Python backend development for financial applications.
- Demonstrated experience designing and maintaining multi-step agentic workflows, orchestration logic, branching execution, and tool use - not limited to simple LLM API calls.
- Practical experience building validation frameworks or testing pipelines to verify AI-generated outputs in a professional setting; concrete examples required.
- Hands-on experience with LLM-powered developer tooling or systems similar to Claude Code, including CLI-based AI agents or LLM-assisted code generation and review pipelines.
- Proven ability to own full system architecture for agentic platforms, covering data flow, tool integration, orchestration, and deployment.
- Strong knowledge of financial risk domains, specifically Market Risk (VaR, ES, Greeks, stress testing, FRTB) and Credit Risk (PD/LGD/EAD, CECL, CCAR, SA-CCR).
- Demonstrated ability to develop scalable, reusable Python libraries.
Preferred Qualifications
- Knowledge of RegIM / SIMM (Regulatory Initial Margin, ISDA SIMM methodology, IM regulatory submissions) is highly desirable.
- Experience with portfolio analytics across multiple asset classes, including derivatives pricing and factor models.
- Proficiency with DevOps tooling: Docker, Kubernetes, cloud platforms (Azure/AWS), and CI/CD pipelines.
- Familiarity with graphical user interface (GUI) development in Python.
- Ability to handle large datasets and implement efficient processing algorithms.
Primary Location Full Time Salary Range of $175,000 - $200,000.
Data Science work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Data Science$170k+
Find me workBy the team behind dataroles.