Quantitative Researcher
1 month ago
Hong Kong, 中国
Millennium
全职
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Quantitative Researcher
Job Description
Quantitative Researcher Job Function Summary We are a systematic trading team dedicated to building a machine-driven investment pipeline that can tackle problems of scale far beyond the reach of traditional systems. Even though we are operating in the financial industry, we are committed to pushing the boundary of human knowledge in related fields such as mathematics, statistics, and machine learning in order to achieve our mission. We are looking for a talented quantitative researcher to join our team. Successful candidate should be capable of developing novel techniques, building unique insights, and making robust systems that will be used in our strategy. One must be able to combine strong technical skills, a passion for creative problem solving, and an intense curiosity about financial markets, science, and human behavior. Principal Responsibilities
• Use disciplined scientific approach to develop quantitative investment models
• Research and develop novel machine learning algorithms
• Develop automated investment models based on peer-reviewed research papers
• Develop unique insights into various datasets
• Use mathematical tools to analyze and optimize trades
• Quantitatively measure and control risk of portfolio
• Apply scientific methods to improve efficiency of trading pipeline Qualifications/Skills Required
• Undergraduates, Masters or doctorate degree in quantitative disciplines, like statistics, mathematics, physics, electrical engineering, or computer science
• Capable of utilizing sophisticated mathematical tools and generalizing it to different contexts
• Strong programming skill in at least one programming language (like Python, C++, or Java)
• Experience analyzing real world problems with disciplined scientific approach
• Capable of following state-of-the-art machine learning and statistics research with no guidance
• Curiosity driven mindset with ability to explore uncharted territory
• Highly motivated and willing to take ownership of work
Job Description
Quantitative Researcher Job Function Summary We are a systematic trading team dedicated to building a machine-driven investment pipeline that can tackle problems of scale far beyond the reach of traditional systems. Even though we are operating in the financial industry, we are committed to pushing the boundary of human knowledge in related fields such as mathematics, statistics, and machine learning in order to achieve our mission. We are looking for a talented quantitative researcher to join our team. Successful candidate should be capable of developing novel techniques, building unique insights, and making robust systems that will be used in our strategy. One must be able to combine strong technical skills, a passion for creative problem solving, and an intense curiosity about financial markets, science, and human behavior. Principal Responsibilities
• Use disciplined scientific approach to develop quantitative investment models
• Research and develop novel machine learning algorithms
• Develop automated investment models based on peer-reviewed research papers
• Develop unique insights into various datasets
• Use mathematical tools to analyze and optimize trades
• Quantitatively measure and control risk of portfolio
• Apply scientific methods to improve efficiency of trading pipeline Qualifications/Skills Required
• Undergraduates, Masters or doctorate degree in quantitative disciplines, like statistics, mathematics, physics, electrical engineering, or computer science
• Capable of utilizing sophisticated mathematical tools and generalizing it to different contexts
• Strong programming skill in at least one programming language (like Python, C++, or Java)
• Experience analyzing real world problems with disciplined scientific approach
• Capable of following state-of-the-art machine learning and statistics research with no guidance
• Curiosity driven mindset with ability to explore uncharted territory
• Highly motivated and willing to take ownership of work