2,048,023open jobs
122,871companies
240,734added this week
Browse all
Salary
$170k – $270k per year
Location
In office (New York)
Seniority
Architect · 4+ years exp

Confirmed on the employer's own hiring board on Nov 2, 2026. First seen by Alion on Oct 1, 2026.

Overview
Company
Impact
Profile match

GIC

GIC is the Singapore sovereign wealth fund, a state-owned global investment firm headquartered in Singapore that manages the country's foreign reserves with the aim of long-term real returns. Established in 1981 on the initiative of Dr Goh Keng Swee, it invests in more than 40 countries across public equities, fixed income, real estate, private equity and infrastructure, employing over 2,000 people in 11 offices including New York, London, San Francisco, Tokyo, Shanghai and Sydney. It hires investment professionals, risk and portfolio analysts, tax and legal counsel, real estate asset managers and a large technology group of software, platform, network and cyber security engineers.

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/

Free account
Stop reading job ads. Get the ones that fit.
One free account turns this page into a shortlist built around your stack, your level and your pay.
Match on every job. Stack, seniority, pay and location, scored against your profile.
2,048,023 open roles. Read straight off company career pages, refreshed every day.
Unlimited applications. Every one you send is tracked in one place, on-site or on a company board.
3 tailored CVs a month. Rewritten for the exact job you are applying to. Included free.
Create a free account Continue with Google
Free forever. No card. Under a minute.

Your match

How well do you fit this role?
Two answers are enough for a real match. No account needed.
Check my fit
Answers stay in this browser until you create an account.

Recommended for you based on this role

Data Science
Similar stack
Same company
New York
$246k – $312k per year · Remote (United States) · Full-Time · United States
Python
Java
SQL
Java
Liquibase
Databases
Snowflake
Apache Kafka
AI/ML
Claude Code
dbt
AI Agents
Feature Store
Analytics
ETL/ELT
Fivetran
Apply
$140k – $200k per year · Equity · In office · Full-Time · 5+ years exp · Denver
Python
SQL
Databases
Databricks
AI/ML
Cursor
Claude Code
MLFlow
Time Series
Interpretability
Machine Learning
Analytics
Tableau
Looker
Apply
Lead Data Architect 11 days ago
$160k – $225k per year · Hybrid · Public Trust · 10+ years exp · McLean
Databases
Snowflake
Databricks
Apache Kafka
AI/ML
NIST AI RMF
DevOps
Terraform
Azure
CI/CD
Git
AWS
Platform Engineering
FinOps
Cybersecurity
FedRAMP
Zero Trust
Analytics
ETL/ELT
Management
Confluence
Jira
Agile
Apply
Lead Data Scientist 11 days ago
$150k – $210k per year · Hybrid · Public Trust · 15+ years exp · PhD · McLean
Python
Databases
Databricks
AI/ML
Spark
Reinforcement Learning
NLP
TensorFlow
PyTorch
Anomaly Detection
Time Series
NIST AI RMF
Machine Learning
DevOps
Azure
CI/CD
Git
AWS
Management
Confluence
Jira
Agile
Apply
Data Engineering Lead 11 hours ago
≈ $112k – $220k per year (Estimated) · In office · Full-Time · Jersey City
Python
SQL
Python
pySpark
Databases
Apache Iceberg
DynamoDB
Amazon Redshift
AI/ML
Spark
DevOps
AWS
Amazon S3
Analytics
ETL/ELT
AWS Glue
Apply
≈ $19k – $44k per year (Estimated) · Hybrid · Full-Time · 8+ years exp · Bengaluru
Python
JavaScript
Java
SQL
Java
Maven
Gradle
Frontend
npm
Mobile
JUnit
DevOps
Rest API
Terraform
Ansible
CloudFormation
Datadog
GitLab CI
CI/CD
Jenkins
AWS
Docker
Kubernetes
Blue-Green Deployment
SRE
Amazon EKS
Amazon EC2
Amazon S3
Windows
Cybersecurity
Snyk
Qualys Cloud Platform
Management
Confluence
Jira
ServiceNow
ITIL
Apply
$160k – $180k per year · In office · Nationals only · 5+ years exp · Bachelor's Degree · Portland
Python
MATLAB
SpaceTech
MBSE
MedTech
Verification & Validation
Defense
MIL-STD-810
MIL-STD-461
Apply
≈ $23k – $45k per year (Estimated) · Hybrid · Full-Time · Bachelor's Degree · Wrocław
Python
SQL
AI/ML
Machine Learning
Apply
AI Engineering Lead 2 days ago
≈ $24k – $62k per year (Estimated) · In office · Full-Time · 16+ years exp · Pune
AI/ML
Claude Code
DevOps
CI/CD
AWS
Management
Agile
Apply
≈ $30k – $52k per year (Estimated) · In office · Full-Time · 4+ years exp · Bachelor's Degree · Gurgaon
Python
SQL
Python
pySpark
Databases
MS SQL
Microsoft Fabric
AI/ML
Spark
DevOps
Azure
Analytics
ETL/ELT
SSIS
Azure Data Factory
Apply
$200k – $280k per year · In office · Master's Degree · New York
Python
SQL
Databases
Databricks
AI/ML
LLM
Streamlit
DevOps
Git
Apply
≈ $49k – $98k per year (Estimated) · In office · 3+ years exp · Bachelor's Degree · Singapore
Python
SQL
Databases
Snowflake
Databricks
AI/ML
Claude Code
AI Agents
LLM
OpenAI Codex
Machine Learning
DevOps
CI/CD
Docker
Analytics
ETL/ELT
Apply
≈ $71k – $165k per year (Estimated) · In office · 7+ years exp · Singapore
Databases
Databricks
AI/ML
LangGraph
LangChain
Claude
Model Context Protocol
Fine-tuning
AI Agents
LLM
GraphRAG
Knowledge Graph
DevOps
CI/CD
AWS
Apply
≈ $69k – $160k per year (Estimated) · In office · 8+ years exp · Bachelor's Degree · Singapore
Python
SQL
PowerShell
Databases
PostgreSQL
Redis
Snowflake
Oracle
MS SQL
Amazon Aurora
Azure SQL Database
DevOps
Terraform
Ansible
GCP
Azure
CI/CD
AWS
Kubernetes
Apply
≈ $69k – $160k per year (Estimated) · In office · Bachelor's Degree · Singapore
Python
SQL
Databases
Databricks
Pinecone
FAISS
OpenSearch
AI/ML
Prompt Engineering
RAG
OpenAI
Anthropic
Hugging Face
DevOps
GCP
Azure
AWS
Apply
Sales Engineer 1 day ago
≈ $114k – $255k per year (Estimated) · Hybrid · New York
Apply
$96k – $128k per year · In office · 8+ years exp · Bachelor's Degree · New York
Design
AutoCAD
Apply
$90k – $125k per year · In office · 8+ years exp · Bachelor's Degree · New York
Design
AutoCAD
Management
Miro
Apply
≈ $231k – $456k per year (Estimated) · In office · Full-Time · 5+ years exp · Master's Degree · New York
Apply
$163k – $220k per year · Equity · In office · Full-Time · 5+ years exp · Bachelor's Degree · Seattle · New York · Santa Clara · Sunnyvale
AI/ML
AWS Bedrock
Machine Learning
DevOps
AWS
Apply
See all jobs
This is one of many
2,048,023 more open roles from verified company boards, updated every day.