Analyst à Grande-Bretagne

Quantitative Research (QR) is an expert quantitative modelling group in J.P. Morgan, as well as a leader in financial engineering, data analytics, statistical modelling and portfolio management. As a global team, QR partners with traders, marketers and risk managers across all products and regions, contributes to sales and client interaction, product innovation, valuation and risk management, inventory and portfolio optimization, electronic trading and market making, and appropriate financial risk controls.

Job summary: As an Analyst or Associate within Quantitative Research, FX Options team, you will have an opportunity to work on developing and maintaining sophisticated mathematical models, cutting-edge methodologies and infrastructure to value and hedge financial transactions ranging from vanilla flow products to complex derivative deals.

Job responsibilities:

• Develop mathematical models for pricing, hedging and risk measurement of derivatives securities
• Contribute to the firm's product innovation, effective risk management, financial risk controls
• Support both OTC and electronic trading activities by explaining model behavior, identifying major sources of risk in portfolios, carrying out scenario analyses, developing and delivering quantitative tools, and researching for new trading ideas
• Assess the appropriateness of quantitative models and their limitations, identifying and monitoring the associated model risk
• Implement risk measurement, valuation models or algorithmic trading modules in software and systems
• Design efficient numerical algorithms and implementing high performance computing solutions
• Design and develop software frameworks for analytics and their delivery to systems and applications
• Write well-formulated documents of model specification and implementation testing

Required qualifications, capabilities, and skills:

• You understand advanced mathematics arising in financial modeling (stochastic calculus, probability theory, partial differential equations, numerical analysis, optimization, statistics)
• You have an advanced degree (PhD, MSc or equivalent) in Engineering, Mathematics, Physics, Computer Science, etc. Relevant academic research publications a plus
• You demonstrate proficiency in code design and programming skills, with primary focus on Python and C++
• You're interested in applying agile development practices in a front-office trading environment
• You quickly grasp business concepts outside immediate area of expertise and adapt to rapidly changing business needs
• You demonstrate quantitative and problem-solving skills as well as research skills
• You're enthusiastic about knowledge sharing and collaboration
• Your excellent communication skills, both verbal and written, can engage and influence partners and stakeholders

Preferred qualifications, capabilities and skills:

• Knowledge of FX Option payoffs and pricing models
• Understanding of the different types of financial risk and you can discuss in detail ways of managing these risks
• Markets experience and general trading concepts and terminology is useful to be familiar with
• Practical data analytics skills on real data sets gained through hands-on experience, including familiarity with methods for working with large data and tools for data analysis (pandas, numpy, TensorFlow)

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law.