Our client is a family investment vehicle and one of the most active private equity investors which is actively investing in diverse sectors in all stages of a company and is part of a conglomerate group.

Description

· Build, test, and validate quantitative investment models using rigorous mathematical, statistical, and computational methods.

· Support the development of systematic equity strategies, including factor-based models, statistical arbitrage, and relative-value approaches.

· Assist in research on derivatives-based strategies, including options pricing, volatility modelling, and hedging.

· Formulate and empirically test research hypotheses, distinguishing robust insights from statistical noise and data-mining biases.

· Acquire, clean, process, and analyse financial, market, and alternative datasets, converting raw data into reliable analytical inputs.

· Build and run back-tests that incorporate realistic transaction costs, market impact, and trading constraints, and check out-of-sample performance and overfitting risk.

· Write reliable, reproducible, and well-documented research code and maintain the team's analytical tools.

· Prepare portfolio and risk analytics covering performance, factor exposures, concentration, liquidity, and market risk.

· Support quantitative due diligence on external fund managers and investment products.

· Prepare clear research notes, technical documentation, and presentations, and present findings and model limitations to the investment team.

Profile

* A master's degree from a reputable university in a highly quantitative discipline such as mathematics, applied mathematics, statistics, physics, computer science, engineering, operations research, finance, or a related field.

* Relevant experience in quantitative research, systematic investing, trading, asset management, derivatives, or financial technology. Strong recent graduates with relevant research or internship experience will be considered.

* A background in economics, finance, financial engineering, or econometrics is desirable but not essential for candidates with exceptional mathematical and computational abilities.

· Strong foundation in mathematics, probability, statistics, linear algebra, and optimisation.

· Strong programming skills, preferably in Python (C/C++ an advantage), with experience in data analysis and statistical or scientific libraries.

· Working knowledge of statistical inference, regression, and time-series analysis; exposure to econometrics or machine learning is an advantage.

· Understanding of out-of-sample testing, look-ahead bias, survivorship bias, and overfitting in investment research.

· Familiarity with version control, reproducible research practices, and working with large datasets.

· Interest in financial markets; familiarity with options, factor models, or portfolio optimisation is an added advantage.

· Clear written and verbal communication, with the ability to explain technical results simply.

Job Offer

• Exciting opportunity to join an investment office to grow their portfolio
• Competitive remuneration package with good culture and benefits
• Great exposure to global markets and multi asset classes

If your quantitative research experience matches this role, please apply.

Michael Page International Pte Ltd. (Company No. 199804751N) is acting as an Employment Agency in relation to this vacancy. To apply online please click the 'Apply' button. For a confidential discussion about this role please contact Gavin Teo (Lic No: R1328332 / EA No.: 18S9099) on +65 6416 9835.