Quantitative Researcher: ML for Trading & Pricing

CMC MARKETS PLC; London Borough of Southwark; On-site; GBP 80,000 - 120,000; Full time

Job summary

CMC Markets plc in London is seeking an ML researcher/quant to advance pricing, forecasting and trading decision support. You will work with developers and trading stakeholders to productionise outputs and monitor model performance in production.

The role requires a quantitative degree and strong Python/SQL along with time-series expertise to deliver reliable research workflows in a regulated trading environment.

Qualifications

• A degree in quantitative finance, mathematics, computer science or equivalent.
• Strong analytical and quantitative research capabilities in trading/front-office environments.
• Experience applying ML/AI techniques to financial/time-series data and feature engineering.
• Strong Python, SQL and time-series analysis skills.
• Experience with Python ML libraries such as scikit-learn, XGBoost, PyTorch or TensorFlow.
• Understanding model governance, explainability and production monitoring in regulated environments.

Responsibilities

• Research, develop and deploy ML/AI models for pricing, forecasting and trading decisions.
• Partner with developers and traders to productionise research outputs and monitor model performance after deployment.
• Translate complex analytical findings into clear recommendations for both technical and non-technical audiences.
• Maintain up-to-date regulatory and governance training and handle confidentiality.
• Design robust experiments and evaluate models with appropriate metrics and cross-validation.

Skills

Time-series analysis

Quantitative research

Experiment design

Model deployment

Education

Degree in quantitative finance / mathematics / computer science

Tools

Python

SQL

scikit-learn

XGBoost

PyTorch

TensorFlow

Job description

CMC Markets plc in London is seeking an ML researcher/quant to advance pricing, forecasting and trading decision support. You will work with developers and trading stakeholders to productionise outputs and monitor model performance in production.

The role requires a quantitative degree and strong Python/SQL along with time-series expertise to deliver reliable research workflows in a regulated trading environment.