Quantitative Researcher
We are seeking a Quantitative Researcher to build, validate, and productionize models across market risk, credit risk, liquidity risk, and climate risk. You will turn financial theory, market data, and regulatory expectations into models that real institutions can use.
- This role is intended for candidates currently based in Malaysia and able to work without visa sponsorship.
- Proficiency in Bahasa Melayu is required (spoken and written).
- This is not a remote role. In-person client and team meetings in Klang Valley are required.
A Malaysia-based risk analytics SaaS startup.
We provide quantitative risk solutions and consulting services to financial institutions, including banks, asset managers, and insurance companies.
Our platform focuses on building industrial-grade quantitative risk engines across market risk, credit risk, liquidity risk, and climate risk, while actively integrating AI and machine learning into risk workflows. In addition to software delivery, we work closely with clients on model design, validation, stress testing, and regulatory-aligned analytics.
As a startup, we work as a small, tight-knit team. This is not an ordinary job. Every team member plays a meaningful role in shaping the product, supporting clients, and growing the company.
Models built for production, not notebooks.
You will work on the quantitative core of Peripamo: model design, calibration, validation, stress testing, scenario analysis, and client-facing explanation. The work spans:
You are not expected to be an expert in every risk type, but you should have strong quantitative fundamentals and the willingness to learn adjacent domains quickly.
This role goes beyond writing formulas. You will work closely with founders, engineers, and clients to make models explainable, testable, and reliable enough for regulated financial workflows.
The successful candidate must be able to attend in-person meetings in the Klang Valley when required.
What you bring.
- Strong proficiency in quantitative finance, risk modelling, statistics, mathematics, financial engineering, or a related field.
- Good understanding of market data (e.g. pricing data, yield curves, volatility, corporate actions, and data quality issues) and how it impacts quantitative models.
- Solid understanding of financial markets, instruments, and portfolio behaviour is preferred.
- Familiarity with derivatives and sell-side instruments, and their risk characteristics (e.g. sensitivities, scenario behaviour) is an advantage.
- Strong foundation in statistics, mathematics, numerical methods, and model validation discipline.
- Proficiency in programming for analytical and system development work, especially Python.
- Ability to translate model assumptions and limitations into clear documentation for technical and non-technical stakeholders.
- Strong problem-solving ability, with attention to detail and numerical accuracy.
- Ability to communicate clearly with both technical and non-technical stakeholders.
- Professional qualifications such as FRM, CQF or CFA (completed or in progress) are an advantage but not required.
Impact matters more than job titles.
- Strong technical curiosity and willingness to learn.
- Comfortable working in a small, fast-moving team.
- Takes ownership and responsibility for outcomes, not just tasks.
- Willing to work across disciplines when needed.
- Communicates clearly and works well with others.
- Understands that in a startup, impact matters more than job titles.
Real models. Real institutions. Real ownership.
- Direct impact Be part of a startup team where your work directly affects the product and company growth.
- Real models, real clients Work on real quantitative models used by financial institutions.
- Cross-disciplinary exposure Gain exposure across quantitative modelling, AI, engineering, and data pipelines.
- Build for production Learn how systems are built, secured, and improved in a real-world environment.
- Grow with the company Opportunity to grow with the company as it scales — both technically and professionally.
Sound like you? Let's talk.
Send your CV and a few lines on your strongest area. We read every application.