- CDI, Plein-temps
- Anson McCade
- Londres, Angleterre, Royaume-Uni
Strats – VP/ED level - London based
My client is a top tier US bank and this team partners with strats, sales, traders, and franchise managers in the FICC market making businesses to understand and quantify opportunities, inefficiencies and workflow obstacles. They develop intuitive and relevant analytics to optimize business leaders' decision making and, partnering with strats, convert data-driven insights into action by embedding those analytics into simple front-line sales and trading workflow tools.
As a front-office Strat on a quickly growing team, you will be at the forefront of a data-driven initiative to optimize decision making across multiple asset classes. You may be building a chatbot that uses Bayesian inference and Natural Language Processing to suggest potential trades, or designing metrics that analyze inquiry and trading activity to enhance client relationships. At times you will be asked to step into the high-pressure environment of the trading floor and at others you will be called upon to guide the decisions of leadership. Whether your interests fall in machine learning, business optimization or full stack development, you will find your calling amidst our diverse team.
This role will draw upon your knowledge of programming and mathematics: you will be challenged to rapidly prototype early-stage solutions and build models-e.g., forecasting the trades and themes our clients may be interested in or predicting the daily trade volume of a bond. Data-driven insights from usage patterns and user feedback will drive you to condense your work into simple and efficient real-time workflow tools. You will also be required to think strategically on a higher level, proposing new business metrics or suggesting alternatives. As you gain expertise in the dynamics of the trading business, you will have the opportunity to dive deeper into your areas of interest.
- BS/MS or PhD in a computational field - Applied Mathematics, Physics, Engineering, Computer Science.
- Quantitative background including an understanding of probability and statistics.
- Strong programming background in compiled or scripting languages (C/C++, Python, Java, etc.).
- At least 6/7 years + experience (financial experience a must).
- Excellent written and verbal communication skills.
- Experience in data science, advanced statistics.
- Familiarity with statistical computing languages or packages (R, numpy/scikit-learn, Matlab).
- Experience with distributed computing.
- Ability to solve problems and explain the ideas that underlie them.
- Confidence to work in a high-pressure environment and deliver results.