USA - Consulting - Financial Services - Quantitative Advisory Services - Senior

USA – Consulting – Financial Services – Quantitative Advisory Services – Senior

The opportunity

At EY Consulting, we are building a better working world by transforming businesses through the power of people, technology, and innovation. Our clients are at the heart of what we do. We’re focused on solving the key issues of our client buyers, building deeper relationships, and generating lasting value with significant impact.

Our firm sets the standard for consulting services, fostering an environment that encourages career ownership at every stage. As a part of our team, you'll be at the forefront of this dynamic service line, driving change and delivering solutions that revolutionize business operations. You’ll help our clients in transformation and innovation efforts: driving growth, reducing costs, and managing risks proactively.

In our Financial Services team, we build a better working world by rallying together to solve the most complex challenges. We accomplish this by building trusted relationships, keeping an open mind, going all in, being bold and courageous, and taking risks worth taking. We help build a financial services industry in which financial institutions are trusted, customers’ financial goals are attainable, and the global economy is growing and secure. In today’s complex business environment, that means understanding the relationship between risk, the regulatory environment, and performance improvement, and applying our knowledge to help clients achieve their business objectives.

Your key responsibilities

In our Financial Services Organization (FSO), the Quantitative Advisory Services (QAS) group operates as an integral component of a broader team that provides comprehensive quantitative risk management services to help identify, measure, manage and monitor the market, credit, operational and liquidity risks , asset-liability management, capital management, and other business activities of our clients across the Banking & Capital Markets, Insurance and Wealth & Asset Management sectors. The QAS team is specifically dedicated to projects focused on development, implementation, testing, validation and other quantitative services of analytic models, which are utilized in, but not limited to:

• risk management including market risk, credit risk (including counterparty credit risk, wholesale, and retail), liquidity / treasury risk, operational risk, compliance risk (including Financial Crime risk), and climate risk

• regulatory capital analytics including Basel III / Fundamental Review of the Trading Book (FRTB), and Comprehensive Capital Analysis and Review (CCAR)

• front office derivative pricing across various asset classes (e.g., interest rate, foreign exchange, equity, credit, commodity and structured products)

• banking book credit analytics, including loss forecasting, reserves/CECL, and PPNR (Pre-Provision Net Revenue)

• balance sheet management

• wealth and asset management

The QAS team also adeptly leverages advanced analytics applications, featuring Artificial Intelligence / Machine Learning (AI / ML), including Generative AI (GenAI), and Natural Language Processing (NLP) capabilities empowering the delivery of unparalleled insights and solutions to the clients.

This is a highly collaborative area, where you’ll always have the support of your team while working on multiple high-profile projects. It’s a challenging specialist area, so we won’t expect you to hit the ground running – you’ll learn as you go. That doesn’t mean you won’t have your own responsibilities though, so if you’re naturally curious, are genuinely interested in this area and are ready to engage with our clients, there’s no limit to how far you can go here.

Skills and attributes for success

To qualify for the role, you must have

• Educational Background: A strong academic record; currently pursuing a PhD in Computational / Quantitative Finance, Mathematics, Engineering, Statistics, Economics, Physics, Computer Science, or a related field; OR a Master’s degree in the same fields with 2+ years of relevant full-time quantitative analytical work experience in mature financial markets.

• Programming Proficiency: Capability to effectively program computer routines using one or more languages such as C++, Java, Python, VBA, SAS, R, and SQL, with a focus on developing algorithms and computational models to solve complex problems.

• Collaborative Teamwork: The ability to work collaboratively in a team environment, demonstrate inclusivity, and embrace diverse perspectives, particularly in cross-functional teams focused on credit modeling and risk management.

• Communication Skills: Excellent presentation skills and the ability to communicate complex concepts effectively to all audiences, including the documentation of risks and models in compliance with regulatory standards.

• Analytical Mindset: Intellectual curiosity, the ability to take initiative and drive execution, with advanced analytical and problem-solving skills within a dynamic and evolving business landscape, particularly in the context of credit risk and model risk management.

• Agile and Growth-Oriented: Exhibits an agile and growth-oriented mindset, with a willingness to adapt to new methodologies and industry practices related to credit and risk modeling.

• Access to reliable transportation to/from the EY office and client sites. A driver’s license is strongly recommended as ride share and public transportation options may not be available in all locations.

• The ability and willingness to travel and work in excess of standard hours when necessary. In certain circumstances, travel may be required beyond your work location based on client and project needs.

Ideally, you will have experience in one or more of the following areas

• Credit Modeling Expertise: Proficiency in credit markets, regulations, and accounting standards related to credit risk, with the ability to develop, apply, build, and calibrate tools and methods associated with credit models that support lending decisions.

• Model Risk Management Knowledge: Familiarity with model risk frameworks, model life cycles, and relevant regulations, along with the ability to document risks and models effectively.

• Quantitative Financial Modeling Skills: Knowledge of and ability to apply advanced statistics and mathematics to financial modeling, risk assessment, and capital management, informed by business domain knowledge.

• Computational Thinking: Understanding of computational models, tools, and techniques to interpret data and formulate solutions, with an emphasis on coding modules and algorithms.

• Risk Modeling Acumen: Knowledge of enterprise risk management, including ESG considerations, operational risk, KYC, AML, fraud, and trade surveillance, with the ability to apply relevant modeling techniques and data sources.

• Knowledge of how to leverage firm-approved AI tools in a business setting, including Microsoft Copilot.