We are looking for a junior quant to join our team in New York within the Model Development team specializing in the asset classes of both Rates and Equities. Its first mission is to develop and maintain sophisticated statistical models and cutting-edge methodologies for risk management and regulatory capital. Its second mission is to analyze the limitations of equities and rates trading pricing models and quantify their impact on Market Risk measures (e.g., VaR, ES, Stress) and on model usage, including documenting findings, recommending mitigations, and supporting governance and controls.

We also work closely with the Quantitative Research teams, Market Risk coverage teams, Technology and Model Risk teams.

As part of the firm’s effort to enhance the strategic risk system, the Model Development team has a strong requirement for new model development, involving significant research and development, and implementation in Python. We are looking for a quantitative Analyst/Associate for a versatile role which mixes vanilla and complex derivatives modelling quant skills with expertise in statistical and data and computer science and AI models.

In addition, we are providing on job training, intensive internal classroom training, and online courses, all given by our experienced team members. Through the diversity of the businesses, it supports and the variety of functions that it is responsible for, Market Risk group provides unique growth opportunities for you to develop your abilities and your career.

If you are passionate, curious and ready to make an impact, we are looking for you.

Job responsibilities

You’ll contribute to the firm’s product innovation, effective risk management, financial risk controls. Specifically, you’ll have the chance to:

• Develop mathematical models for risk measurement of both derivatives and securities;
• Carry out research projects into innovative methodologies or improving the existing Market Risk and Regulatory Capital framework;
• Assess the appropriateness of quantitative risk management models and their limitations, identifying and monitoring the associated model risk;
• Support our model users by explaining model behavior, identifying major sources of risk in portfolios, carrying out scenario analyses, developing and delivering quantitative tools, and researching for new innovative models;
• Analyze limitations of equity and rates trading pricing models and potentially quantify their impact on Market Risk measures (VaR, ES, Stress, Limits) and on model usage
• Contribute to documentation, controls, and governance processes.

Required qualifications, capabilities, and skills

• You demonstrate quantitative and problem-solving skills as well as research skills.
• You understand advanced mathematics arising in financial modelling like probability theory, stochastic calculus, statistics.
• You have excellent 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, scikit, Tensor Flow);
• You have strong foundations in AI and and large language models (LLMs); Prompting: zero-shot, few-shot, chain-of-thought, grounding and context management; Retrieval-augmented generation (RAG) and vector search basics.
• You bring computer programming experience such as Python or Github copilot.
• You’re enthusiastic about knowledge sharing and collaboration.
• You have strong interpersonal skills – you listen and communicate in a direct, succinct manner.
• You have an advanced degree (PhD, MSc, or equivalent) in Engineering, Mathematics, Physics, or Computer Science.
• You’re interested in market risk from risk management and regulatory capital perspectives.
• You are familiarity with general risk management concepts and terminology (e.g., VaR, ES).
• You understand the different types of risk and you can discuss in detail ways of managing these risks.

Preferred qualifications, capabilities, and skills

• You have an advanced degree (PhD, MSc, or equivalent) in Engineering, Mathematics, Physics, or Computer Science.
• You’re interested in market risk from risk management and regulatory capital perspectives.
• You are familiarity with general risk management concepts and terminology (e.g., VaR, ES).
• You understand the different types of risk and you can discuss in detail ways of managing these risks.