Quantitative Trading Engineer

1 week ago

Singapore SYNTHIFY TECH PTE. LTD. Full time

**Quantitative Trading Engineer / Quantitative Researcher**

Working day: Monday to Friday, 9am to 6.30pm

Working location: Raffles Place

**Salary**: Discuss during interview

**Responsibilities**

**Strategy Development**:

- Use AI technologies such as machine learning and deep learning to intelligently optimize investment strategies and improve the performance of strategies in actual transactions.

**Data Analysis：**
- Collect and analyze large financial datasets (market data, news, social media, etc.).
- Work with large data sets to predict and test statistical market patterns, combining knowledge of systems, mathematical techniques, and trading to identify the best places to improve the trading system.Build and optimize feature engineering pipelines to improve model prediction accuracy.

**Financial Modeling**:

- Construct, back-test, maintain, and improve financial models to support trading activities.
- Conceptualize valuation strategies, develop, and continuously improve upon mathematical models and help translate algorithms into code
- Conduct research and statistical analysis to build and refine monetization systems for trading signals
- Optimize the order execution and risk management of our trading system
- Create robust solutions to problems presented in the trading environment
- Build 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**:

- Backtest historical data to evaluate the strategy's yield, volatility, drawdown and other indicators.
- Deploy the strategy to the real-time environment, track performance and continuously optimize.

**Requirements**:

- Master’s degree or above in Statistics, Mathematics, Applied Mathematics, Computer Science, Financial Engineering or equivalent.
- At least 2 years of experience in quantitative trading and machine learning modeling.
- Proficient in programming languages such as Python, C++, Java, etc.
- Familiar with common machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn.
- Familiar with quantitative trading systems, data flows and algorithms.
- Deep understand the structure of financial markets and be familiar with markets such as virtual currencies, stocks, futures, and foreign exchange.
- Experience in large-scale data processing, proficient in using SQL, NoSQL, Hadoop and other tools.

**Bonus Skills**
- Experience in developing high-frequency trading strategies will be an advantage.
- Participated in AI competitions (such as Kaggle) or published papers in top conferences (such as NeurIPS, ICML) will be an advantage.
- Familiar with cutting-edge AI technologies such as reinforcement learning, and generative adversarial networks (GANs) will be an advantage.

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