The Core Engineering- Quantitative Engineer -Associate / Vice President - London

Goldman Sachs; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Goldman Sachs in London seeks a quantitative analyst to join Corporate Treasury. You will design and implement ALM models, forecast net interest income, and support liquidity and funding decisions with rigorous risk analysis.

You will develop stress tests, backtesting, and behavioural models for deposits and channels, while presenting findings to senior management and cross-functional partners in a global team.

Qualifications

• Masters or PhD in a quantitative field (math, physics, econ, CS) preferred.
• Strong programming skills in Python, C++, or Java.
• Proven experience in a quantitative finance role focusing on ALM or balance sheet management.
• Excellent written, verbal, and collaborative communication skills.

Responsibilities

• Design, implement, and maintain ALM models and tools for NIM forecasting and EaR.
• Develop stress-testing frameworks across portfolios to assess performance under market scenarios.
• Build behavioural models for deposits and channels under rate scenarios.
• Establish backtesting and data quality processes to monitor model performance.

Skills

Python

C++

Java

Quantitative finance

Communication skills

Independent work

Education

Masters preferred

PhD preferred

Tools

AI tools

Job description

About Corporate Treasury

Corporate Treasury manages the firm’s liquidity, funding, balance sheet and capital to maximize net interest income and return on equity through liability planning and execution, financial resource allocation, asset liability management, and liquidity portfolio management. The division is run by the Global Treasurer and works closely with the CFO, each of the firm’s businesses, Controllers, Operations, and Investor Relations among other groups at the firm. The division is ideal for collaborative individuals with strong quantitative analysis skills, interest in portfolio & liquidity management and risk management mind set.

Job Responsibilities

• Design, implement, and maintain quantitative models, tools, and frameworks for Asset Liability Management (ALM) including Net Interest Margin (NIM) forecasting, Earnings-at-Risk (EaR), and funding cost projections to optimize resources
• Develop stress and scenario analysis frameworks across portfolios, products, and legal entities to assess performance under a range of market scenarios identifying and quantifying key risk exposures, concentration risks, convexity effects, and potential vulnerabilities.
• Develop and enhancing behavioural models for deposits and other channels, such as non-maturity deposit modelling, deposit beta estimation, repricing lags, and volume flow projections under different macro scenarios and interest rate environments.
• Establish rigorous backtesting, model performance monitoring, and data quality frameworks to continuously evaluate model accuracy, identify potential drift, and refine behavioural and forecasting assumptions.
• Develop and uplift models to reflect evolving business needs, maintain model documentation and implementation, and support regulatory inquiries and second-line model validation.
• Deliver clear presentations and explanations related to balance sheet management for discussion with senior managers, committees, and key stakeholders.

Qualifications

At Goldman Sachs, we think who you are makes you better at what you do. We seek out people with excellent quantitative and communication skills. Here are some of the qualities we look for:

• Excellent academic background in a quantitative field such as mathematics, physics, statistics, economics, engineering, or computer science, with a preference for Masters and PhDs.
• Strong programming skills in an object-oriented or functional paradigm such as Python, C++, or Java.
• Proven experience in a quantitative finance role, with a strong focus on ALM, funding modelling, behavioural modelling, or balance sheet management.
• Solid understanding of fixed income instruments, interest rate derivatives, curve construction methodologies, pricing/hedging strategies and their application to balance sheet risk management.
• Deep understanding of statistical and econometric modelling techniques (e.g., regression analysis, time-series forecasting, survival analysis) applied to financial products. Experience using AI-based tools in development is a plus.
• Excellent written, verbal, and team-oriented communication skills, with the ability to explain complex quantitative concepts to non-technical stakeholders.
• A self-starter with the ability to work independently as well as thrive in a collaborative, global team environment.

About Goldman Sachs

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

The Goldman Sachs Group, Inc., 2026. All rights reserved.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.