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Quantitative Research Engineer

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2年近く前に更新

職務内容

Ephod Technology is a FinTech startup focus on helping global money managers to make better decisions with the help of quantitative analysis.The investment research industry is heavily manpower dominated. Industry research reports, company financial models and trading strategies are mostly analyzed by human. In EphodTech, we work together as a team to disrupt the industry to modernize the decision making process of money management.

We are now working with fund managers in Hong Kong, Mainland China, and Taiwan for building our MVP product. We are now building a core engineering team to accelerate our development process.

Your Responsibilities:

  • Identify valuable data sources, and analyze the trends and patterns to exploit market inefficiencies
  • Present information using data visualization techniques
  • Build predictive trading signal models with machine learning algorithms

職務要件

  • Bachelor or higher degree from a leading university in a highly analytical field (i.e. Computer Science, Financial Engineering, Mathematics, Electrical Engineering, Physics)
  • Have a strong interest in learning about worldwide financial markets in a quantitative way
  • Knowledge of statistical and machine learning frameworks (e.g. Python, R, Pandas, TensorFlow, Scikit, Pytorch)
  • Trading or finance working experience is a plus
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4
1,000,000 ~ 2,000,000 TWD / 年
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私たちについて

Ephod Technology is a FinTech startup focus on helping global money managers to make better decisions with the help of quantitative analysis.

Ephod Intelligence is a Software as a Service (SaaS) platform designed to assist fundamental research analysts in validating their investment ideas and keeping a close watch on the equity market. By incorporating analysts' unique investment strategies, Ephod employs sophisticated, non-linear quantitative models to identify and recommend the most effective stock screening factors. This approach allows for the generation of personalized trading signals based on the proposed factors.




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