Quantitative Researcher – Machine Learning
Location: London, UK
Compensation: Competitive
Company: Equity-Focused Asset Manager
We are looking for a Quantitative Researcher to join our Machine Learning team, working on the development and optimization of mid-to-low frequency equity trading signals. This role offers the opportunity to work across the full research pipeline, from exploratory data analysis and idea generation to predictor construction, performance evaluation, and portfolio optimization. The successful candidate will also contribute to production-level code, monitoring signals and portfolios to ensure robustness and effectiveness.
Key Responsibilities:
Stock Ranking & Signal Development – Utilize machine learning techniques to develop predictive models for stock ranking and selection.
Portfolio Construction – Apply quantitative methods to optimize portfolios that compete with discretionary portfolio managers.
Research & Development – Work on innovative approaches to equity trading signals, including:
Discrete optimization on computational graphs to automate predictor/portfolio searches.
Text-based NLP techniques to score datasets (e.g., earnings call transcripts, news).
Standard quantitative techniques to identify mean reversion and momentum opportunities.
Production & Monitoring – Assist in writing production-ready code and monitor predictors and portfolio performance.
Ideal Candidate:
Strong background in machine learning
Experience with predictive modeling and signal development for financial markets.
Knowledge of portfolio construction techniques.
Proficiency in Python and/or other quantitative programming languages.
Previous experience in an equity-focused quant fund or asset management firm.
This is an opportunity to work with an industry-leading quant team, leveraging proprietary datasets and state-of-the-art machine learning techniques to develop and deploy innovative investment strategies.
To apply, please submit your resume to quantresearch@octaviusfinance.com