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. 

We are looking for an exceptional Data Scientist to join the Data Search & Analytics team. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of data at the firm.

Your future role within QRT

This team is integral to the firm’s success. As such, your responsibilities will include:

• Collaborating with Quantitative Researchers and Traders to design datasets that drive systematic strategies and to inform discretionary trading decisions
• Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats
• Working with Engineers to automate and optimise your code, ensuring robust data extraction processes
• Managing the end-to-end process of onboarding new datasets
• Proactively solving data related problems to minimise time to production
• Innovating and experimenting with novel data extraction methods to enhance the firm’s data onboarding toolkit

Your present skillset

• 3+ years of experience as a Data Scientist (or similar position); experience in a buy-side quantitative finance role is advantageous
• Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering.
• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy
• Demonstratable interest in financial markets and the application of data in its analysis and understanding
• Experience working with both traditional and alternative financial datasets
• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors
• Ability to work in a high-performance, high-velocity environment

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

About Cubist

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role

Data Scientists bridge the gap between raw data and predictive modelling. We believe everything starts with data. You will work closely with our quantitative research team, applying advanced techniques to engineer, validate, and refine features that feed directly into our systematic models. This is a role within an established investment team, offering opportunities for progression into more senior research responsibilities across the full trading pipeline.

Responsibilities

• Conduct thorough data analysis under the mentorship of a senior quantitative researcher.
• Generate novel ideas for enhanced proprietary data products.
• Track and evaluate new offerings from internal and external data vendors in partnership with Compliance.
• Transform firm approved raw datasets into robust features for our systematic models.
• Build analytical tools to supplement our shared research framework.

Requirements

• BS, MS or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline.
• Programming in Python (or a comparable language) and working knowledge of SQL.
• Strong analytical and quantitative skills.
• Willingness to take ownership of their work.
• Ability to work both independently and collaboratively within a team.
• Strong desire to deliver high quality results in a timely fashion.
• High attention to detail.
• Prior experience as a data analyst, data sourcing specialist, or data scientist for a financial firm is a plus
• Commitment to the highest ethical standards.