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.
