Systematic Machine Learning Quant Researcher (Machine Learning)
at TECHNOLOGY SERVICES GROUP PTE LTD
Singapore, Southeast, Singapore -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 08 Nov, 2024 | USD 7000 Monthly | 09 Aug, 2024 | N/A | Physics,Machine Learning,Publications,Reinforcement Learning,Deep Learning,Mathematics,Finance,Financial Engineering,Learning Techniques,Statistics,Computer Science | No | No |
Required Visa Status:
Citizen | GC |
US Citizen | Student Visa |
H1B | CPT |
OPT | H4 Spouse of H1B |
GC Green Card |
Employment Type:
Full Time | Part Time |
Permanent | Independent - 1099 |
Contract – W2 | C2H Independent |
C2H W2 | Contract – Corp 2 Corp |
Contract to Hire – Corp 2 Corp |
Description:
Leading AI quant fund are looking to hire a machine learning quant researcher onto their systematic team.
REQUIREMENTS:
- Masters/PhD degree in Mathematics, Physics, Financial Engineering, Computer Science, Statistics with specialization in Machine Learning
- Experience working with large datasets and machine learning techniques
- Experience in one or more of deep learning, reinforcement learning, non-convex optimization, Bayesian non-parametrics, NLP or approximate inference.
- Publications at top conferences such as NeurIPS, ICML, ICLR etc. is highly desirable.
- Experience in a high-performance language (ideally C++, or similar languages)
- Outstanding performance in any quantitative field or contest (Kaggle, hackathons, Olympiads, academic contests etc.).
- Experience implementing machine learning algorithms in industry.
- Open to ML quants who are already working within finance or ML quants within tech who are interested to move to finance.
- Trading Background is not a pre-requisite for the above role.
Responsibilities:
- Conduct quantitative research with PM and other AI quants to develop and back-test different machine learning and statistical models, as well as productionize such models.
- Combine sound financial insights and machine learning techniques to explore, analyze, and harness a large variety of datasets.
- Use a rigorous scientific method to develop sophisticated trading models and shape our insights into how the markets will behave.
- Apply machine learning to a vast array of datasets
- Focuses on Regression and Classification
- Focuses on EnsemblesUnderstanding confidence interval, probability inference and causal inferences
REQUIREMENT SUMMARY
Min:N/AMax:5.0 year(s)
Information Technology/IT
IT Software - Other
Software Engineering
Graduate
Machine learning
Proficient
1
Singapore, Singapore