Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.
Your future role within QRT
In this role, you will serve as a key contributor to our financial data research efforts. You will handle extraction and processing of data from various financial sources like websites, PDFS, and other ad hoc sources. Your work will play a crucial role in ensuring that traders, quant researchers, and technology teams have access to accurate and timely data, facilitating informed decision-making across the organization.
Key Responsibilities:
- Conduct in-depth research analysis of financial data from multiple sources, including Bloomberg, Thomson Reuters Eikon, S&P Capital IQ, FactSet, and others,
- Define robust processes to manually collect data from complex documents along with PDFs, images, and audio files, requiring a solid understanding of the subject matter documents and other relevant platforms.
- Actively track news and updates across various sectors, and share key insights on a daily and weekly basis, including relevant links.
- Leverage strong experience in Excel macros and VBA coding to further enhance data handling and automation processes.
- Collaborate closely with cross-functional teams to understand data needs and ensure that the right data is provided in a user-friendly format.
- Monitor data accuracy and resolve any discrepancies or issues that may arise.
- Provide support and guidance to users on utilizing the data effectively for their respective needs.
- Stay updated with the latest trends and tools in financial data research, automation, and alternative data sources.
- Exposure to and potential involvement in projects related to Large Language Models (LLMs) or ChatGPT, enhancing the data interaction experience.
Your Present Skill Set:
- Bachelor’s degree in finance, Computer Science, Data Science, or a related field.
- Proven experience in financial data research and analysis, with a strong understanding of financial markets and instruments.
- Experience with data sources such as SEC EDGAR, earnings calls, and alternative data platforms like Quandl.
- Excellent analytical skills, with attention to detail and a strong focus on accuracy.
- Ability to work collaboratively with traders, quant researchers, and technology teams.
- Effective communication skills, both written and verbal, with the ability to present complex data in a clear and concise manner.
- Exposure to Python scripts to automate the extraction, processing, and validation of financial data from various sources, with an emphasis on cleaning and normalizing data inconsistencies, such as improperly formatted fields in Excel or CSV files.
- Exposure to Large Language Models (LLMs) or ChatGPT is a plus.
