Quantitative Researcher

Point72 Careers; London; On-site; GBP 60,000 - 100,000; Full time

Job summary

An innovative firm is seeking a talented researcher to explore systematic anomalies in global macro markets. This role involves rigorous research, feature engineering, and managing the research pipeline, including data processing and modeling. Ideal candidates will have a strong background in mathematics, statistics, and machine learning, along with proficiency in programming languages like Python or R. Join a team dedicated to ethical standards and collaborative research in a fast-paced trading environment, where your contributions will drive impactful trading strategies and enhance portfolio performance.

Qualifications

• 2+ years of experience in signal research for macro trading.
• Proficiency in Python, R, or C/C++ and data science toolkits.

Responsibilities

• Conduct innovative research to identify systematic anomalies in macro markets.
• Manage the research pipeline from data processing to strategy backtesting.

Skills

Mathematics

Statistics

Machine Learning

Quantitative Finance

Data Manipulation

Collaborative Mindset

Education

Degree in Mathematics or Statistics

Degree in Computer Science or Engineering

Degree in Economics

Tools

Python

R

C/C++

scikit-learn

Pandas

Job description

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/RESPONSIBILITIES

• Perform rigorous and innovative research to discover systematic anomalies in global macro markets (futures, FX, etc.)
• Perform feature engineering with price-volume, order book and alternative data at intraday to daily horizons in mid frequency trading space
• Perform feature combination and monetization using various modeling techniques
• Manage the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
• Maintain and improve portfolio trading in a production environment
• Contribute to the analysis framework for scalable research

REQUIREMENTS

• Background in mathematics, statistics, machine learning, computer science, engineering, quantitative finance, or economics
• 2+ years of signal research experience in macro trading as part of a trading team
• Prior professional experience with feature engineering, modeling, or monetization
• Ability to efficiently format and manipulate large, raw data sources
• Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas
• Strong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniques
• Collaborative mindset with strong independent research abilities
• Commitment to the highest ethical standards