- Internships & Graduate Trainee, Full time
- Société Générale - VIE
- 09 Nov 18
- Hong Kong
- Selon profil
- Full time
Quantitative Research - M/F VIE Hong Kong
Identify, record, clean and validate structured and unstructured datasets as asource of information· Research alphas: design, model and test predictive statistical models· Work on risk management, risk/reward optimization and risk constraints· Develop code of trading models to run backtests on statistical market-makingstrategies with holding horizons from intraday to weeksSG CIB is the Corporate and Investment Banking arm of the Societe Generale Group.
Present in over 50 countries across Europe, the Americas and Asia.SG CIB provides
corporate, financial institutions, investors and public sector clients with value-added
integrated financial solutions.
As a Quantitative Researcher in the Asia QMM team (quantitative market-making),
you will be trained by senior quants to research and test systematic trading
strategies. You will learn how to apply your mathematical/statistical skills to this
growing field of financial markets.
Your main responsibilities and missions will be :
* Identify, record, clean and validate structured and unstructured datasets as a source of information
* Research alphas: design, model and test predictive statistical models
* Work on risk management, risk / reward optimization and risk constraints
* Develop code of trading models to run backtests on statistical market-making strategies with holding horizons from intraday to weeks
The VIE assignment in a nutshell
This VIE in Hong Kong is to begin as soon as possible but you need to plan 3 months between your application date and the beginning of your VIE assignment. It will last 12 months.
The VIE is a specific contract, under Business France's eligibility criteria, opened to candidates under 28 and from the member states of the European Economic Space. For further information, please see www.civiweb.com.
Profil recherché :
You are graduated with a Master degree from Engineering or Business School or University with a specialization in Mathematics, Statistics, Computer Science, Physics or similar.Advanced knowledge in probability and statistics
Prior experience in data-driven quantitative research will be an advantage.You are fluent in English.You are proficient in Microsoft Office application (Excel, powerpoint).Object oriented languages (with a preference for C#) and Statistical / analytics programming languages (with a preference for R and Python) are required.