Quantitative Researcher

Aargo Trade; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Aargo is seeking an outstanding Quantitative Researcher to join our quantitative trading team in London. You will collaborate with quantitative traders and developers to create novel systematic trading strategies and leverage our research infrastructure.

You will apply cutting-edge statistical, machine learning and deep learning methods to financial data to learn patterns and predict market behavior, contributing to alpha signals, portfolio construction and advanced modeling.

Qualifications

• Experience applying statistical, machine learning and deep learning to financial data.
• Deep understanding of financial markets and market micro-structure.
• Exceptional analytical and problem solving skills.
• Proficiency with Python data libraries for analysis and modeling.
• Ability to own projects with minimal supervision.
• Bachelor's degree in computer science, mathematics, statistics, data science or related quantitative field.

Skills

Statistical ML on financial data

Financial markets knowledge

Analytical problem solving

Python data stack

Project ownership

Education

Bachelor's degree in Computer Science, Mathematics, Statistics, Data Science or quantitative field

Tools

pandas

numpy

scikit-learn

statsmodels-tsa

TensorFlow

Keras

Matplotlib

Job description

Aargo is looking to add an outstanding Quantitative Researcher to one of our quantitative trading teams. Quantitative Researchers collaborate extensively with quantitative traders and quantitative developers to create and build novel systematic trading strategies. Our quantitative researchers leverage our state of the art research infrastructure to apply rigorous statistical and mathematical methods on a variety of data. They use cutting edge statistical, machine learning and deep learning algorithms to learn from the data and use this intelligence to predict the future market behavior. The candidate can expect exposure to a wide range of interesting and challenging problems including alpha generation, portfolio construction, statistical modeling, machine learning, and deep learning.

Required Core Competency

• Hands-on experience in applying statistical, machine learning and deep learning methods on noisy financial data for creating novel alpha signals
• Deep understanding of financial markets and market micro-structure
• Exceptional analytical and problem solving skills
• Expertise in using pandas, numpy, scikit-learn, statsmodels-tsa, TensorFlow, Keras, and Matplotlib libraries for data analysis
• Comfortable taking ownership of projects and responsibilities with minimum supervision
• At least a bachelors degree in Computer Science, Mathematics, Statistics, Data Science or other quantitative discipline

Good to Have

• Experience in developing tools and libraries for market data analysis and back-testing
• Prior experience at a top tier hedge fund, proprietary trading house or investment bank