Market Risk Financial Ingenieur — Trafigura
CHF 60'500 - 91'500
Trafigura · Geneva (GE)
- Ort
- Geneva
- Vertrag
- full-time
- Veröffentlicht
- vor 31 Tagen
LohnCHF 60'500 - 91'500
Rollenüberblick
Main purpose
We are looking for a highly motivated Market Risk Analyst to join Trafigura’s Market Risk team at the intersection of commodity trading and cutting-edge AI.
This role goes beyond traditional risk analysis: you will harness agentic AI to build automated workflows, design analytical tools, and deliver rapid, high-quality insights that directly support trading decisions across our Oil & Petroleum Products, Metals, and Power & Gas divisions.
- Main purpose
- We are looking for a highly motivated Market Risk Analyst to join Trafigura’s Market Risk team at the intersection of commodity trading and cutting-edge AI.
- Key responsibilities
- Design and deploy agentic AI workflows to automate data ingestion, analysis pipelines, risk reporting, data analysis, and P&L pipelines — dramatically reducing manual effort and accelerating time-to-insight across the team
Hauptaufgaben
- Key responsibilities
- Design and deploy agentic AI workflows to automate data ingestion, analysis pipelines, risk reporting, data analysis, and P&L pipelines — dramatically reducing manual effort and accelerating time-to-insight across the team
- Champion agentic AI adoption across the market risk function — building a shared library of reusable AI agents and engineering frameworks that multiply the team’s output
- Stay at the frontier of agentic AI — LLM orchestration, tool-use, multi-agent architectures — continuously evaluating and introducing new capabilities to our workflows
- Develop, rewrite, and expand code for quantitative risk models and metrics (VaR, Greeks, P&L attribution) across commodity asset classes
- Build and maintain scalable, containerised data pipelines for daily ingestion and analysis of market data, ensuring accuracy, completeness, and timeliness.
- Validate data quality and enforce rigorous standards across market data ingestion pipelines; escalate and resolve production issues (data quality, limit breaches, pipeline failures)
Bewerbungsprozess
- Stay current with developments in agentic AI — LLM orchestration, tool-use, multi-agent architectures — and actively evaluate their application to our workflows and risk processes. Required qualifications
- Minimum 2–4 years’ experience in market risk, quantitative finance, or a related analytics role within commodity trading or financial services.
- Expert-level Python programming skills; additional proficiency in F# or C++ is a strong advantage.
- Demonstrated, hands-on experience building or deploying agentic AI — LLM APIs, agent frameworks (e.g.
- LangChain, AutoGen, Claude API, custom tool-use pipelines), or multi-agent orchestration.
- This is a core requirement, not a nice-to-have.
- Deep understanding of market risk concepts and metrics: VaR, Greeks, stress testing, scenario analysis, and P&L attribution.
- Expertise in CI/CD pipelines, containerised environments (Docker/Kubernetes), and software architecture best practices.
Weitere Details
- Stay current with developments in agentic AI — LLM orchestration, tool-use, multi-agent architectures — and actively evaluate their application to our workflows and risk processes.
- Excellent English communication skills (oral and written, native or equivalent to C2 level), with the ability to convey technical concepts clearly to both engineers and business stakeholders.
- Prior exposure to multi-commodity environments spanning oil, metals, and power/gas markets, and familiarity with the associated market data providers and conventions. Attributes for success
- AI-first mindset : genuinely excited by agentic AI and actively seeks opportunities to deploy it across the team’s workflows — not just as a personal productivity tool but as shared infrastructure that multiplies the team’s output.
Notizen und Originalinhalt
- Prior exposure to multi-commodity environments spanning oil, metals, and power/gas markets, and familiarity with the associated market data providers and conventions.
- Attributes for success
