The Equities Analytics team works with Equities sales-trading desks to analyze and optimize our clients' and the firm's execution strategies across Equities products globally.
The group is responsible for the development and maintenance of the Analytics and Research Platform used by Equities. The platform provides the following functionality:
- Collects and enriches massive amounts of data resulting from execution of client and firm trades and market data.
- Analytical tools to monitor and analyze Execution Algorithm performance both on a real-time and historical basis and deliver analysis to clients
- Big Data platform to perform market microstructure research to develop and optimize Equities Execution algorithms
- Analytical tools to provide transparency and insight to management and senior stakeholders on how Equities products are used by clients.
- Design, build and maintain a high-performance, high-availability, high-capacity, yet nimble and adaptive platform for transaction cost analytics and execution research
- Develop highly reliable data ingestion processes to consume large volumes of data emitted by trading and market data systems.
- Design distributed computation infrastructure and libraries to run parallelized queries over large volumes of data.
- Design, build and maintain applications to monitor performance of trading strategies in relation to the market in real time.
- Use data to guide decision-making, developing or enhancing tools as necessary to collect it.
- Communication with traders, sales, clients and compliance officers about new feature requests, explanation of existing features etc.
- Bachelors or Master's degree in computer science or engineering or equivalent experience
- 1 to 2 years of professional experience in a data engineering/analytics role
- Experience with Python/Java/C++ based large scale streaming data analytics and storage solutions
- Experience with Equities transaction and market data, Transaction Cost Analytics
- Strong communication skills and the ability to work in a team
- Strong analytical and problem solving skills
- Experience in data driven performance analysis and optimizations.
- Experience building streaming data processing and ingestion pipelines
- Experience building distributed data processing systems which handle a high volume of client queries
- Knowledge and Experience with KDB
- Strong knowledge of object oriented programming, data structures, algorithms and design patterns
- Prior experience building systems used by multiple technical and non-technical teams
- Over 3 years' experience in Financial industry
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