As a Quantitative Researcher at Quance Research Capital LLP, you will play a pivotal role in developing and testing automated quant trading strategies using sophisticated statistical techniques. Your responsibilities will include designing high-frequency trading strategies by analyzing market data, identifying patterns, exploring market inefficiencies, and developing algorithms to capitalize on opportunities that exist for a fraction of a second. You will have access to market data from various exchanges worldwide and will be expected to conceptualize strategies, continuously improve mathematical models, and translate algorithms into code. Your role will involve modeling gigabytes of data daily, utilizing Python, R, and C++ to analyze market microstructure and identify trading signals. You will also be responsible for improving existing trading strategies, back-testing and implementing new models in a live trading environment, conducting statistical analysis to refine monetization systems, and producing business-critical reports. Additionally, you will trade a vast portfolio and work towards enhancing the organization's trading strategies across global exchanges. To excel in this role, you should possess a deep quantitative/programming background with a graduate degree in Statistics, Engineering, Computer Science, Mathematics, Operations Research, Economics, or a related quantitative field. A minimum of 2 years of experience, preferably in High-Frequency Trading (HFT) or Algo firms, is required. Strong knowledge of probability and statistics, as well as proficiency in Python, R, and C++, is essential. Familiarity with data science, machine learning, market microstructure, and Linux will be advantageous. We are seeking self-motivated individuals with a keen interest in financial markets, commodities, and machine learning/AI techniques. If you have expertise in ML-based systems and a passion for trading, we encourage you to apply. Strong analytical skills, attention to detail, ability to work under pressure, and a collaborative mindset are crucial for success in this role. Join us at Quance Research Capital LLP and be part of a dynamic team driving innovation in the financial markets.,
As a Quantitative Researcher at Quance Research Capital LLP, you will be responsible for developing and testing automated quant trading strategies using sophisticated statistical techniques. Your role will involve designing high frequency trading strategies with access to market data from various exchanges worldwide. You will analyze data, identify patterns, explore market inefficiencies, and create algorithms to capitalize on opportunities that exist for just a fraction of a second. It is crucial that the algorithms you develop are highly efficient to ensure success in the fast-paced trading environment. Key Responsibilities: - Conceptualize, develop, and enhance mathematical models to translate algorithms into code - Analyze gigabytes of data daily from various exchanges using Python, R, and C++ to identify micro behavioral patterns - Study market microstructure to discover trading signals and opportunities based on order flow - Collaborate with the team to improve existing trading strategies and enhance performance metrics like latency and PnL - Back test and implement trading models and signals in a live trading environment - Conduct research and statistical analysis to refine trading signal monetization systems - Manage a vast portfolio and develop essential business reports Qualifications Required: - Graduate degree (Bachelors, Masters, PhD) in Statistics, Engineering, Computer Science, Mathematics, Operations Research, Economics, or a similar quantitative field - Minimum of 2 years of experience, preferably in High-Frequency Trading (HFT) or Algorithmic trading - Strong knowledge of probability and statistics, with expertise in machine learning, time-series analysis, pattern recognition, and NLP - Proficiency in Python or R, C++, data science, machine learning, and market microstructure - Working knowledge of Linux is preferred - Prior trading experience is beneficial but not mandatory - Experience in a data-driven research environment and a keen interest in Machine Learning/AI techniques - Excellent analytical skills, attention to detail, and the ability to work under pressure and in a team environment If you possess expertise in ML-based systems, a passion for financial markets, and trading, we encourage you to apply for this exciting opportunity at Quance Research Capital LLP.,
As a Quantitative Researcher at Quance Research Capital LLP, you will play a crucial role in designing and implementing high frequency trading strategies. You will have access to market data from various exchanges worldwide and be expected to analyze the data, identify patterns, and explore market inefficiencies to develop algorithms that can capitalize on these opportunities. Your primary responsibilities will include: - Designing high frequency trading strategies based on market data analysis - Conceptualizing, developing, and enhancing mathematical models to translate algorithms into code - Analyzing and testing gigabytes of data daily using Python, R, and C++ to identify micro behavioral patterns - Exploring market microstructure to discover trading signals and opportunities through predictive modeling - Collaborating with the team to improve existing trading strategies and implement new ideas - Backtesting trading models in live environments to assess latency and performance metrics - Conducting research and statistical analysis to refine monetization systems for trading signals - Managing a diverse portfolio and generating business critical reports To excel in this role, you should possess the following qualifications: - A graduate degree (Bachelors, Masters, PhD) in Statistics, Engineering, Computer Science, Mathematics, Operations Research, Economics, or a related quantitative field - Minimum of 2 years of experience, preferably in High-Frequency Trading (HFT) or algorithmic trading - Strong knowledge of probability, statistics, machine learning, time-series analysis, and pattern recognition - Proficiency in Python or R, C++, data science, machine learning, and market microstructure - Working knowledge of Linux is preferred - Prior experience in trading is beneficial but not mandatory - Familiarity with data-driven research environments and interest in Machine Learning/AI techniques - Excellent analytical skills, attention to detail, and ability to work under pressure both independently and in a team setting If you have expertise in ML-based systems, a passion for financial markets, and a desire to contribute to a dynamic team environment, we invite you to apply for this exciting opportunity at Quance Research Capital LLP.,