Responsibilities: Perform quantitative research and data analysis on trade, quote, and alternative datasets for US corporate bonds, municipal bonds, EM hard currencies and fixed income ETFs, generate signals and evaluate how it can be applied. Research, develop and back-test various quantitative models to predict bond prices, bid-ask spreads and expected turnover. Trade US corporate bonds and emerging market hard currencies to build inventory for ETF creation process, monitor and analyze performance profit and loss. Build real-time model to price multiple ETF NAVs for daily ETF trading. Engage in fixed income ETF primary market in kind create/redeem process and design baskets for standard redeem. Research on commodities futures spread trading strategy, end to end manage a proprietary commodities book. Work with developers to monitor and ensure that diverse datasets are properly ingested, easy to use and delivered in real-time. Work with team members to apply predictive models in trading and marketing to share findings, and collaborate on ad hoc requests to ensure research results are fully monetized.

Required Skills: Applicant must possess a Bachelor’s or foreign equivalent degree in engineering, statistics, mathematics, or in a related quantitative field and 18 months of experience as a Quantitative Analyst. Additionally, the applicant must have professional experience in the following:

• Building Quantitative models with a proven track record of deploying such models to production in a team-driven environment
• Fixed Income research and development, modelling bond prices and bid-ask spreads
• Knowledge in fixed income securities, including duration, and interest rate
• Working with large datasets and fluency in python programming including pandas, scikit-learn, matplotlib, and seaborn
• Supervised and unsupervised Machine learning modelling
• Time Series modelling
• Computer programming with Python, R, VBA, Linux, Git, Vim, and SQL