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Analyst / Associate - Quantitative Strategist - Trading - Instinet - Hong Kong
May 20, 2020
Nomura is an Asia-based financial services group with an integrated global network spanning over 30 countries. By connecting markets East & West, Nomura services the needs of individuals, institutions, corporates and governments through its three business divisions: Retail, Asset Management, and Wholesale (Global Markets and Investment Banking). Founded in 1925, the firm practices disciplined entrepreneurship while building on a long tradition of serving clients with creative solutions and considered thought leadership.
As the agency-model execution services arm of the Nomura Group, Instinet Incorporated subsidiaries provide brokerage services to clients in over 65 markets around the world. Through its advanced suite of electronic trading strategies, experienced high-touch trading group, top-ranked Commission Management services, award-winning desktop trading platform, and unparalleled access to insightful analytics, content and unique liquidity, Instinet helps institutions lower overall trading costs and ultimately improve investment performance. For more information, please visit www.instinet.com.
PURPOSE AND SUMMARY
Instinet's Global Trading Research (GTR) group, responsible for the firm's algorithmic trading and quantitative analysis platforms, is intensifying its focus on execution performance. As part of this effort, we are seeking a talented and experienced quantitative strategist, working in Hong Kong.
The successful candidate will join the Quantitative Trading Strategy (QTS) team and will be required to use their quantitative talents and experience in the Asia-Pacific equities execution domain, to drive revenue through execution quality.
The role involves projects spanning the entire cycle from the inception of an idea, to quantitative research, finally A/B-testing. The ideal candidate will have proven experience in applying quantitative analysis to the equities market, but other domains will be considered. Prior experience in equities trading, algorithmic trading, market making or market micro structure will be highly advantageous
This is a highly visible role and would suit a highly capable practitioner with a deep passion for data analysis, scientific endeavor and algorithmic trading.
Perform research on trading outcomes to measure contextual efficacy of various trading strategies.
Perform and interpret Trade Cost Analysis (TCA) and use this to drive trading ideas.
Design models to more effectively use trading tactics to achieve strategic performance, and work closely with engineering team to implement the models.
Be involved in algorithmic trading from inception of idea to research to quantitative follow-up.
Improve quantitative performance of trading algorithms as measured internally.
Improve quantitative performance of trading algorithms as measure by clients.
Key Experience & Skills
PEOPLE & PROJECT SKILLS
Deep intellectual curiosity and passion for data.
Excellent communication and presentation skills with excellent command of the English language.
Strong team player with willingness to both teach others and learn new approaches.
Proven ability to collaborate and succeed in a global team a plus.
Demonstrable ability to implement practical applications of quantitative research.
Experience with large-scale data analysis.
Experience and knowledge of Asian market micro-structure and strategies.
Experience applying quantitative analysis in computer languages such as Python, R, SQL, Scala or Java.
Experience of Trade Cost Analysis (TCA) a clear advantage.
High-frequency trading experience, e.g. in market making, proprietary or agency space a clear advantage.
Excellent degree in a scientific discipline e.g. Statistics, Mathematics, Physics, Machine Learning or Computer Science.
0-5 years of working experience.
Regional Disclaimers / Diversity Statement
Nomura is committed to an employment policy of equal opportunities, and is fundamentally opposed to any less favourable treatment accorded to existing or potential members of staff on the grounds of race, creed, colour, nationality, disability, marital status, pregnancy, gender or sexual orientation.