Credit Suisse - Electronic Trading Role

We are a dynamic high-energy team that continually demonstrates a rare mix of quantitative and technology skills to build disruptive electronic tradable products to manage business revenue while efficiently managing operational risk, and ensuring control standards are of the highest level. Our three core areas are (1) Electronic & Systematic Risk Trading (2) Quantitative Pricing (3) Data.

Trading:

We built the ETF Nitro platform, one of the largest off-exchange cross -product, dynamic auto-hedging and automated risk-trading platforms for ETFs on the street. The platform prices block liquidity, and hedges orders in fractions of a second by tapping into various sources of liquidity. We aim to build, fine-tune, and improve technologies and quantitative strategies to effectively systematically trade risk across different product types.

Pricing:

We developed a suite of quantitative models and a pricing platform, which systematically prices hundreds of ETFs covering over 20K stocks, 80 currencies and across over 100 exchanges.

Data:

Data sourcing, managing, and analytics is a huge part of what we do. We use different sources of data, in addition to our synthetically derived prices, in doing quantitative analytics with the aim of improving our trading and pricing platform. Data ware-housing, enrichment, consolidation, structuring, and normalization for millions of data points across thousands of ETFs & Indexes is part of our day-to-day function.

Job Details:

You will contribute to developing innovative electronic trading quantitative analytics, technologies and products. As our team is small and very entrepreneurial, we are very results driven and believe every member (from the most junior to the most senior) brings a unique value and is pivotal to the team's success.

Core Requirements

- 5+ years of experience

- PhD in Engineering, Mathematics, Econometrics, Computer Science, Physics, or a core science field- from a top-tier school

- Ability to develop mathematical models to solve stochastic problems

- Some understanding of Market Microstructure

- Exposure to ETF/Futures/Index Theoretical Pricing

- Execution Algorithms - VWAP, TWAP, Vol-Inline, Implementation Shortfall, etc.

- Knowledge of Futures and Equity Execution venues

- Good experience working on trading signal generation, back-testing, and idea conceptualization

- Reading of academic literature and research papers/ journals to identify potential new ideas for real-world execution and also to add improvements to existing investment and trading models

- Index Futures rolls analytics

- Experience working with either or all of Matlab, R, Python

- Exposure to tick data analysis

- Publication in machine learning, financial forecasting, optimization, signal processing, operations research or related field

- Experience applying machine learning methodologies to solving complex problems

- Good programming skills

- Some exposure to an object oriented programing language

- Experience conducting research with large datasets

- Passion for applying quantitative analytics to solving real world problems

Additional - Platform/Product Development

- Developing and maintaining interactive analytical tools to help traders make investment decisions

- Helping the technology team for product development with requirements and testing.

- Review/enhancements of existing risk and pricing models

- Bespoke Custom Basket analytics tools

- Systemize the Rebalances, corporate actions, funding and dividend forecasting and integrate it with the swap pricing models