Quantitative Engineer

Summary

We are looking for a Quantitative Engineer to develop and implement advanced quantitative models that drive investment and trading strategies across multi-asset financial markets. This role focuses on applying data-driven methodologies, including machine learning, statistical modeling, and algorithmic trading, to optimize portfolio management, risk assessment, and market forecasting. The ideal candidate possesses strong programming skills, a deep understanding of financial markets, and expertise in quantitative research, enabling them to design innovative solutions for complex investment challenges.

Job Responsibilities

• Develop quantitative algorithms for portfolio optimization, risk mitigation, and financial modeling.
• Utilize computing techniques such as machine learning and Monte Carlo simulations to enhance market forecasting and trading strategies.
• Research and design algorithms to improve asset allocation, liquidity management, and financial risk strategies.
• Collaborate with investment analysts, data scientists, and financial strategists to integrate solutions into investment platforms while ensuring regulatory compliance.
• Apply quantitative methodologies to enhance risk management strategies for equities, commodities, and cryptocurrency markets.

• Hold a Bachelor’s or Master’s degree in Financial Engineering, Computer Science, or Mathematics.
• Possess strong knowledge of financial markets, investment strategies, and risk management.
• Have experience in data acquisition, quantitative modeling, and application development in a research or financial environment.
• Be well-versed in at least one asset class, such as equity, fixed income, or high-yield bonds, with a track record in financial research and software development.
• Have familiarity with quantitative analytics, including fund performance measurement, predictive risk modeling, and alpha research.
• Possess strong analytical skills to process large datasets, detect anomalies, and develop innovative financial solutions.
• Have expertise in logical data modeling and relational database design for financial applications.

• Supportive teammates
• Health insurance benefits
• Self development activities that support careers
• Hybrid working arrangement