Operational risk manager
Il y a 2 mois
ArcelorMittal is a leading steel producer with a worldwide footprint and annual sales reaching ~$80bn a year. Guided by a philosophy to produce safe, sustainable steel, it is the leading supplier of quality steel products in all major markets including automotive, construction, household appliances and packaging. ArcelorMittal operates in 60 countries and employs ~170 000 people worldwide. Within Corporate functions, ArcelorMittal Treasury is the central treasury of the Group, acting as the internal bank of the Group, facing financial markets to deal with all corporate finance and price risk management matters. Scope of assets under management, number of subsidiaries managed by Treasury and structure of the cash pooling make AM Treasury one of the most elaborate and sophisticated corporate treasuries.
Within the Financial Risk Management Department, Risk Assessment and Measurement team (RAM) is in charge of i) providing appropriate quantitative analysis of the market and /or financial structures for risk management purpose, ii) to develop financial models to analyse market price evolution, for pricing/accounting purpose and for elaborating trading strategies supporting financial optimisation, and iii) analysing and monitoring the exposure at-risk the Group is bearing through its industrial and financial operations.
As a Quantitative Risk Analyst within the RAM team, you will play a pivotal role in developing advanced quantitative models, optimizing risk management processes, and enhancing risk assessment across various asset classes. You will also be responsible for interpreting complex data to provide actionable insights that drive strategic decision-making.
Responsibilities:
Traders & MO Collaboration: Work closely with traders and MO to create appropriate risk tools to associate risk measures (VaR, ES, XVaR etc) to trading/hedging ideas and communicate them to top management for implementation decision and/or limit monitoring
Model Development and Refinement: Lead the development and refinement of complex financial models for risk management and simulation across various asset classes and improve all type of VaR estimation methods (historical, monte-carlo, cornish-fisher etc)
Cross-Asset Risk Calculation: Develop models to calculate risk measures and perform stress tests on a diversified portfolio comprising miscellaneous underlying assets and products and identify the risk associated to all the different layers (Asset Class/Underlying/Individual Trade)
Risk System Development: Design and implement our risk system by using object-oriented program such as Python, C++ or Java and create PowerBI reports for data illustration
Quantitative Daily Activities: Actively participate in treasury tasks (reports, documentation etc) and other quantitative topics as they emerge, collaborating with various teams and addressing diverse subjects such as tax, accounting, front office, and financing
Stress Tests: Perform stress tests and calculate sensitivity matrices for various risk factors to evaluate the potential impact of extreme market conditions on the company's financial health
Business Understanding: Understand the global context of steel production to define and derive appropriate trading and hedging strategies linking financial and physical flows
Technical Environment Enhancement: Collaborate with data scientists, quantitative researcher, traders, and IT professionals to improve and enhance the technical environment, incorporating new technologies
Mentorship and Guidance: Mentor and guide junior analysts, fostering a culture of continuous learning and improvement
Database Enhancement and Documentation : Improve our databases' data and schema within the Databricks environment, develop and maintain scripts on Git, and ensure comprehensive documentation of all processes and changes
Continuous Monitoring: Continuously monitor the performance of the risk models, making adjustments as necessary to adapt to changing market conditions and maintain sustainability
Required Education and Experience:
Education: Master’s degree required with a strong academic background in financial markets or quantitative fields with a financial market orientation (Financial Engineering, Machine Learning, Computer Science, Mathematics with an understanding of stochastic processes)
Experience: Previous experience in a Hedge Fund, Bank, or Corporate quantitative front office team is advantageous
Market Knowledge: Understanding of market drivers and fundamentals of financial markets
Model knowledge: Knowledge of derivative products and developing simulation tools (Monte-Carlo and other numerical simulation models, statistical analysis tools such as ACP, financial pricing models, etc.)
Financial Tools Familiarity: Familiarity with Bloomberg and Refinitiv is a plus
Language Skills: Fully proficient in English, both verbal and written. Fluency in French is a plus
Technical Skills: Strong knowledge of Python, SQL, Databricks, PowerBI, M, DAX, PySpark, VBA, Git other data analysis tools (C++ would be a plus)
Additional Skills Required:
Entrepreneurial Spirit: An innovative mindset with a willingness to propose solutions
Functional Testing: Use methods for conducting and monitoring the functional testing of an application
Detail Oriented: High attention to detail and strong critical thinking/analytical skills
Relationship Building: Ability to build relationships and interface effectively with all levels of the organization
Spirit: Team player with the ability to solve problems efficiently with other collaborators and show confidence when presenting
What We Offer:
An opportunity to work within a leading global organization with a commitment to innovation and sustainability
Free access to an on-site gym and shower facilities throughout the day
A dynamic and collaborative work environment with a focus on professional growth and development.
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