G
Quantitative Researcher
G
Quantitative Researcher
good job creations (singapore) pte. ltd.- Posted 4 days ago
- Be among the first 10 applicants
Job Description
[Job ID: 1643909]
About the Role:
We are seeking a Quantitative Researcher to develop and enhance trading and investment strategies across international markets. You will leverage data-driven approaches, programming tools, and statistical models to build robust quantitative strategies.
Responsibilities:
- Research and develop international market, secondary market trading and investment strategies
- Use programming and analytical tools to drive quantitative strategies through continuous iteration
- Extract patterns from market microstructure, trading data, fundamentals, events, and multivariate data
- Build and refine diversified quantitative strategy models
Requirements:
- Bachelor's degree or above in Finance, Mathematics, Computer Science, Engineering, or related field
- Proficiency in Python, C++, or other high-level programming languages
- Strong communication and learning abilities
- Experience in quantitative research within a hedge fund or similar environment
- Experience using big data to predict and test statistical market models
- Background in AI/ML research for quantitative analysis
- Participation in competitions such as Kaggle, ILSVRC, IMO, IOI, IPhO, or similar
We regret that only shortlisted candidates will be notified. However, rest assured that all applications will be updated to our resume bank for future opportunities.
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EA Personnel Name: Cesky Ong Zhi Rong
EA Personnel Registration Number: R24121422
EA License No.: 07C5771
More Info
About Company
Skills:
Ml, Deep Learning, programming, Python, Data Analysis, LLMs, financial data structures, Ai, reinforcement learning, Statistics, time-series analysis, statistical methods
Skills:
Java, Rust, C++, Python, Back testing, On-chain data, Machine-learning methods, Real-time market-data systems, Research infrastructure, Data pipelines, Simulation, Exchange APIs
Skills:
Machine Learning, Python, large-scale data analysis, backtesting simulation frameworks, signal generation techniques, statistical arbitrage
Skills:
Pandas, Excel, Sql, Python, Scikit-learn
Skills:
Python, C++, Deep Learning, modern deep learning architectures, LLM tooling, experiment tracking, regularization, efficient columnar formats, experiment-management tooling, hyperparameter optimization, throughput profiling and optimization, ensembling, machine learning theory, Optimization, large-scale datasets, mixed precision, Statistics, reproducible research environments, large-scale model training, distributed multi-GPU training, CUDA-level optimization, point-in-time-correct dataset construction, streaming data loaders