Quantitative Trading Engineer

3 weeks ago


Singapore SYNTHIFY TECH PTE. LTD. Full time $7,500 - $12,000

Working Day and Location

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

Working location: Raffles Place

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.
  • Extract predictive signals from financial data through both traditional statistical analysis methods and cutting-edge machine learning techniques.
  • Formulate and apply mathematical modeling techniques to enhance existing trading strategies and perform innovative new research with the goal of identifying and capturing trading opportunities.
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 understanding of 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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