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Quantitative Trading Expert
1 month ago
Raise your career to the next level with Synthify Tech PTE. LTD., a leading player in the finance industry. As an esteemed Quantitative Trading Engineer/Quantitative Researcher, you will play a pivotal role in driving our company's success.
The job involves working on a standard Monday-to-Friday, 9am-to-6.30pm schedule at Raffles Place. The estimated salary for this position is SGD $120,000 per annum, based on market standards and comparable roles in Singapore.
Key Responsibilities:
We are seeking a skilled professional to join our team as a Quantitative Trading Engineer/Quantitative Researcher. Key responsibilities include:
- Developing AI-powered investment strategies using machine learning and deep learning techniques to enhance trading performance.
- Extracting predictive signals from financial data through statistical analysis and cutting-edge machine learning methods.
- Applying mathematical modeling techniques to optimize existing trading strategies and identify innovative research opportunities.
Data Analysis:
The successful candidate will be responsible for:
- Collecting and analyzing large financial datasets, including market data, news, and social media feeds.
- Working with massive data sets to predict and test statistical market patterns, combining knowledge of systems, mathematical techniques, and trading to identify areas for improvement.
- Building and optimizing feature engineering pipelines to improve model prediction accuracy.
Financial Modeling:
This role requires a strong background in:
- Constructing, back-testing, maintaining, and improving financial models to support trading activities.
- Conceptualizing valuation strategies, developing, and continuously improving upon mathematical models and translating algorithms into code.
- Conducting research and statistical analysis to build and refine monetization systems for trading signals.
- Optimizing the order execution and risk management of our trading system.
- Creating robust solutions to problems presented in the trading environment.
- Building regression, classification, reinforcement learning, and other models for market forecasting and trading decisions.
- Tuning the model's hyperparameters to improve model performance and stability.
Strategy Backtesting and Real-Time Testing:
The ideal candidate should have experience in:
- Backtesting historical data to evaluate the strategy's yield, volatility, drawdown, and other indicators.
- Deploying the strategy to the real-time environment, tracking performance, and continuously optimizing.
Requirements:
To be considered for this role, applicants must meet the following criteria:
- Hold a Master's degree or above in Statistics, Mathematics, Applied Mathematics, Computer Science, Financial Engineering, or equivalent.
- Have at least 2 years of experience in quantitative trading and machine learning modeling.
- Be proficient in programming languages such as Python, C++, Java, etc.
- Familiarity with common machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn.
- Familiarity with quantitative trading systems, data flows, and algorithms.
- A deep understanding of the structure of financial markets and familiarity with markets such as virtual currencies, stocks, futures, and foreign exchange.
- Experience in large-scale data processing, proficiency in using SQL, NoSQL, Hadoop, and other tools.
Bonus Skills:
Candidates with the following skills will be given preference:
- Experience in developing high-frequency trading strategies.
- Participation in AI competitions (such as Kaggle) or publication of papers in top conferences (such as NeurIPS, ICML).
- Familiarity with cutting-edge AI technologies such as reinforcement learning and generative adversarial networks (GANs).
In return for your expertise, we offer a competitive salary package and a dynamic work environment that fosters growth and innovation.