We are a premier global financial institution with a flagship cross-border payment and trade finance franchise. Headquartered in Singapore for Asia-Pacific operations, we manage over USD multi-billion in cross-border liquidity portfolios, serving institutional and corporate clients across the world's major trade corridors. Our platform operates a fully modular financial intelligence infrastructure spanning vertical industry research, payment data mining, trade financing product engineering, foreign exchange risk quantification, and AI agent-driven automation layers. We are now expanding our core modeling team in Singapore and invite expert-level talents with deep financial research rigor and AI engineering mindset to join us in building next-generation cross-border financial intelligence systems.
Our target expert does not produce generic market commentary. Instead, you will generate actionable quantitative signals and automated decision logic by systematically deconstructing cross-border trade flows, payment data streams, and currency fluctuation cycles. Every payment data point, every regulatory update, and every exchange rate movement becomes an input to your research framework—delivering continuous, intellectually engaging challenges.
Key Responsibilities
Vertical Industry Systematic Research
- Conduct full-chain in-depth research on cross-border payments, international trade finance, FX markets, and cross-border data industries—covering industry sizing, growth space assessment, and market ceiling analysis.
- Dissect data production mechanisms, core data sources, and industry ecosystem structures; synthesize application scenarios, implementation cases, and business model evolution trends.
- Map full-link compliance risks, regulatory boundaries, and policy constraints; evaluate industry cost structures, economic models, and investment return profiles.
- Deliver systematic industry frameworks, risk catalogs, and implementation standards to serve as the knowledge foundation for internal model training and strategy iteration.
Payment Data Mining & Cross-Border Financing Demand Modeling
- Build intelligent analytics models based on cross-border transaction data, cash flow characteristics, and corporate payment behavior—automatically identifying financing gaps, business pain points, and credit potential of import/export enterprises.
- Trace root causes of client capital pressure and construct customer segmentation and demand labeling systems for precision financing profiling.
- Design and optimize intelligent financing solutions across import financing, export financing, letter of credit packing loans, international factoring, and cross-border BNPL.
- Continuously track global payment industry trends, regulatory policy updates, and business model changes to iterate model logic and product strategies.
Foreign Exchange Risk Quantitative Modeling
- Independently build quantitative risk infrastructure for cross-border financial business, including: FX exposure measurement models, exchange rate sensitivity analysis frameworks, cross-border risk early warning systems, and stress testing/scenario simulation mechanisms.
- Enable fully quantifiable, monitorable, and predictable cross-border risk management—upgrading FX risk from qualitative judgment to quantitative decision-making.
Financial Business AI Agent Full-Stack Development
- Lead the construction of a vertical cross-border financial AI agent system, integrating industry research logic, payment mining rules, trade financing product logic, risk measurement models, and compliance standards into automated intelligent workflows.
- Deliverables include: intelligent business diagnosis and financing need identification, automated financial solution generation, automatic exposure calculation and risk tiering/early warning, pre-scenario compliance verification, and dynamic industry review with strategy iteration mechanisms.
- Drive the engineeringization of research logic, ensuring agent outputs are accurate, interpretable, and capable of business-loop closure.
Exclusions (Not Included in This Role)
No business development, sales negotiation, client relationship maintenance, offline due diligence, documentation processing, channel execution, administrative, operational, or marketing tasks.
Mandatory Requirements
- 5+ years of research/modeling experience in cross-border payments, international trade finance, or FX risk management, with background at buy-side financial institutions, major bank cross-border business units, or tier-1 fintech core modeling teams.
- Deep mastery of at least two of the following three core domains, with basic familiarity with the third: ① Cross-border payment industry research and data mining; ② Trade finance product design and credit modeling; ③ FX risk measurement and exchange rate forecasting.
- Advanced proficiency in Python/R for data mining, feature engineering, time-series analysis, and user behavior modeling; solid experience with quantitative backtesting frameworks and model validation processes.
- Hands-on experience with LLM applications, RAG (Retrieval-Augmented Generation), and AI agent workflow design—with proven ability to translate complex financial logic into engineeringized agent modules.
- Excellent structured thinking and systematic logic capabilities; self-motivated with independent deep research ability; thrives in a highly focused, research-intensive work environment.
- Master's degree or above in Financial Engineering, Quantitative Economics, Computer Science, Data Science, or related discipline. CFA/FRM charterholders preferred.
Preferred Qualifications
- Experience developing AML compliance models for cross-border payments or trade fraud detection models
- Track record of building internal credit default prediction models or financing demand forecasting models
- Familiarity with SWIFT, Ripple messaging systems, and ISO 20022 standards
- Demonstrable track record of translating model signals into actual business decisions in collaboration with trading desks or business lines
- Prior experience designing internal research infrastructure—data pipelines, monitoring dashboards, or backtesting platforms
Compensation & Benefits
We offer a highly competitive compensation package tailored to top-tier cross-border financial research talent, based in Singapore's financial district.
- Base Salary: SGD 180,000 – SGD 300,000 per annum, commensurate with research depth, modeling capability, and business impact
- Performance Bonus: 60% – 200% of base salary, directly tied to model signal accuracy, AI agent automation conversion rates, and risk-adjusted return contribution to the business
- Total Annual Compensation: SGD 288,000 – SGD 900,000+ (uncapped upside) for exceptional performers; candidates with outstanding track records may negotiate above range
- Infrastructure Access: Full access to proprietary cross-border payment databases, global FX data terminals, trade credit risk monitoring systems, top-tier sell-side research networks, and international financial conference resources
- Career Trajectory: Clear pathway to Core Modeling Team Lead, Head of Cross-Border Strategy, or transition to Quantitative Portfolio Management for high-performing candidates
Application Instructions
Please submit your resume together with:
- Research Framework Summary (1–2 pages): A systematic articulation of your core methodology in cross-border financial research—covering your approach to industry research frameworks, payment data mining logic, financing need identification systems, and FX risk measurement, as well as how you prioritize signals across different macro-trade regimes.
- Representative Research Outputs (3 items): For each, include—market/business context, analytical methodology, specific model signal or agent logic recommendation, and post-implementation P&L attribution or business outcome assessment with quantifiable metrics.
- Optional but Highly Valued: A description of any proprietary tools, models, or AI-assisted workflows you have built to automate or enhance cross-border financial research processes.
Equal Opportunity Employer – Applications reviewed on a rolling basis until the position is filled.
