Responsibilities
· Develop quantitative models and algorithms for Trading, including order execution, market making, and alpha generation.
· Deliver well-documented prototype and production code to run financial models, mainly in Python and Scala.
· Create software applications, user interfaces, APIs, dashboards, and automated reports for business users.
· Assist with Business Development, including writing Data Analytics mandate, preparing reports, and delivering business presentations.
· Understand and clearly present Quantitative Finance literature.
· Create technical reports, and appropriately document developed libraries.
· Assist, when needed, with the development of Data Analytics platform, including Databases and Data Lake.
· Collaborate with Data Scientists, Developers, and Traders to jointly meet deadlines.
Qualifications & Skills
· Master or PhD in a technical field, such as Quantitative Finance, Mathematics, Physics, Engineering, Economics, Computer Science, or alike.
· 3+ years of work experience as a Quantitative Analyst / Quantitative Developer in a financial firm.
· Advanced coding skills in programming languages such as Python, R, Matlab, Haskell, Scala, C++, and/or Java.
· Experience in Quantitative Trading, for example developing systematic strategies.
· Knowledge of Mathematical Finance and Financial Markets, including Algorithmic Trading, Derivative Pricing, Portfolio and Risk Management, Dynamic Programming, and Numerical Methods.
· Knowledge of Machine learning methodologies, including Clustering techniques, Factor Modelling, Reinforcement Learning, and Advanced Statistics.
· Knowledge of Git, SQL, and Dash (or similar).
· Basic knowledge of PowerBI, Tableau, and VBA.
· Experience with Real Time Analytics, Low-Latency Algorithms, Webapp Development, Docker, Kubernetes, etc. is a strong plus.
· Experience with Business Development is a plus.
· Collaborative, team player, open minded, and easy to work with.
· Proficient presentation skills and high attention to detail.
· Able to explain technical results to non-technical audiences.