AVP/VP, Quantitative Strategist, Structured Product Group

Job Function: Fixed Income & Multi Asset

Job Type: Permanent GIC is one of the world’s largest sovereign wealth funds. With over 2,000 employees across 11 locations around the world, we invest in more than 40 countries globally across asset classes and businesses. Working at GIC gives you exposure to an extraordinary network of the world’s industry leaders. As a leading global long-term investor, we work at the point of impact for Singapore’s financial future, and the communities we invest in worldwide. Fixed Income and Multi Asset Our team employs a broad range of investment strategies that span macro, credit, and quantitative investing, including multi-asset, benchmark-agnostic, constrained, indexed, and thematic strategies. Structured Products Group (SPG) Our investment purview spans across residential mortgages, consumer credit, and other sectors such as aircraft, insurance-linked securities, and agriculture. We create an edge by leveraging extensively on data and technology in our investment process. What impact can you make in this role? We are seeking a Quantitative Strategist to join our Structured Product Group, focusing on Agency and Non-Agency securitized products across residential, consumer, and commercial sectors. The role supports portfolio managers and investment teams through quantitative analysis, modelling, data workflows, and tools used for deal evaluation, portfolio monitoring, stress testing, collateral analysis, and relative value assessment. The successful candidate should combine structured-products knowledge, strong coding ability, practical data-management skills, and the judgement to translate analytical work into investment-relevant insights. What will you do as a Quantitative Strategist? Risk Analysis: Understand the mechanics and risk drivers of structured products, including cashflows, prepayments, credit performance, collateral characteristics, duration, convexity, and spread behaviour. Prepayment Modelling: Build, calibrate, and validate prepayment models for Agency and Non-Agency residential mortgages, developing insight into borrower, servicer, and lender behaviour, and explaining variance between empirical and modelled prepayment performance in terms of underlying market and policy drivers. Quantitative Techniques: Apply quantitative and statistical methods to support valuation, OAS analysis, scenario analysis, stress testing, and relative value assessment. Financial Modelling: Develop and maintain Python‑based models and analytical tools for cashflow analysis, portfolio monitoring, deal evaluation, and risk diagnostics. Collateral Analysis: Analyse loan‑level and collateral data, including pool characteristics, vintage performance, issuer behaviour, delinquency trends, and other drivers of securitized‑products performance. Data Management: Work with large and complex datasets from internal systems, market data and analytics platforms (e.g., Intex, Bloomberg, Yield Book), loan‑level data providers, servicers, and external research sources; build repeatable workflows and data‑quality checks. Communication: Explain model outputs, assumptions, limitations, risk drivers, and investment implications clearly to portfolio managers, analysts, risk managers, and technology partners. Collaboration: Partner with investment, quantitative, data, and technology teams to improve analytics, production reliability, workflow automation, and decision support across global locations. What qualifications or skills should you possess in this role?

Required qualifications: 4-8 years of relevant experience in quantitative/structured-products roles, including direct experience developing or working with residential mortgage prepayment models. Bachelor's or master's degree in a quantitative field such as Mathematics, Statistics, Physics, Engineering, Computer Science, Financial Engineering, Economics, or a related field. Strong programming skills in Python, with the ability to write clean, reliable, and maintainable code. Experience handling large datasets, databases, APIs, cloud‑based data platforms, and data‑quality controls, including familiarity with tools such as AWS, Databricks, or agentic workflow tools. Solid understanding of fixed income and structured‑products concepts, including cashflows, spread, OAS, duration, convexity, prepayment risk, credit risk, and stress testing. Familiarity with Agency and Non‑Agency securitized products across residential, consumer, or commercial sectors. Ability to perform cashflow modelling, collateral analysis, sensitivity analysis, and scenario analysis. Understanding of the sensitivity of structured products and portfolios to macro factors such as interest rates. Understanding of how to measure liquidity, including TRACE trading volume, outstanding amount, and other liquidity indicators. Strong problem‑solving skills, with the ability to debug data or model issues independently and propose practical solutions. Excellent communication skills, with the ability to translate quantitative analysis into investment‑relevant insights and explain complex quantitative and technical concepts to non‑technical stakeholders. Resourceful, self‑directed, and comfortable working across teams and global locations.

Preferred qualifications: Direct experience building or validating agency mortgage prepayment models (e.g., logistic, hierarchical, structural, or mixed‑effects approaches), and experience with Non‑Agency RMBS, ABS, CMBS, securitized‑products cashflow models, or structured credit analytics. Exposure to leading mortgage/structured-products analytics and modelling platforms, whether from the buy side or from a vendor modelling team, such as Intex, Bloomberg (BAM), Yield Book, or BRS/Aladdin. Experience working with loan‑level mortgage data from providers such as CoreLogic (Loan Performance), Black Knight/ICE McDash, or eMBS. Experience building production or semi‑production analytics, dashboards, data pipelines, or investment tools. Experience with collateral stratification, deal tape analysis, waterfall modelling, or scenario engines. Interest in applying automation, AI, or modern data tools to investment research, collateral surveillance, and workflow improvement. Work at the Point of Impact We need to be forward‑looking to attract the right people to help us become the Leading Global Long‑term Investor. Join our ambitious, agile, and diverse teams – be empowered to push boundaries and pursue innovative ideas, share your views, and be heard. Be anchored on our PRIME Values: Prudence, Respect, Integrity, Merit and Excellence, which guides us in how we make our day‑to‑day decisions. We strive to inspire. To make an impact. Flexibility at GIC At GIC, our offices are vibrant hubs for ideation, professional growth, and interpersonal connection. At the same time, we believe that flexibility allows us to do our best work and be our best selves. Thus, our teams come into the office four days per week to harness the benefits of in‑person collaboration, but have the flexibility to choose which days they work from home and adjust this arrangement as situational needs arise. We are an equal opportunity employer As an employer, we passionately believe every individual brings with them unique diversity of thought and perspectives to meaningfully enrich perspectives of GIC teams to drive competitive performance. An inclusive environment yields exceptional contribution. Compensation Our compensation philosophy reflects several principles. We strive to provide a competitive compensation package to attract and retain talent globally. We pay for performance, and reward sustainable results. Total pay for this position comprises base pay and bonus. The anticipated base salary range for this role is between $170,000 and $270,000. Bonuses, which may form a meaningful proportion of the total pay package, are determined based on company and individual performance. Learn more about our Human Resource & Organization Department here: https://gic.careers/departments/portfolio-execution-solutions-group/