4 of 4 Risk Analytics Jobs in London

Engagement: Represent the organization at finance-focused conferences and forums to promote responsible AI adoption. Compliance Alignment: Ensure all AI solutions meet strict regulatory, risk, and ethical standards in financial services. Prototyping & Deployment: Build and deploy AI models for market forecasting, risk analytics, automated underwriting ...

Engagement: Represent the organization at finance-focused conferences and forums to promote responsible AI adoption. Compliance Alignment: Ensure all AI solutions meet strict regulatory, risk, and ethical standards in financial services. Prototyping & Deployment: Build and deploy AI models for market forecasting, risk analytics, automated underwriting ...

Machine Learning Engineer/ML Engineer Machine Learning Development Design and implement machine learning models for financial applications, with a focus on pricing and risk analytics Build scalable ML pipelines for processing large-scale financial data Develop deep learning architectures for time series prediction, anomaly detection, and pattern … requirements and identify ML opportunities Develop data-driven approaches to complement traditional quantitative finance models Support implementation of ML solutions for derivatives pricing and risk management Core Technical Skills Machine Learning Expertise : Deep understanding of ML algorithms (supervised/unsupervised learning, reinforcement learning) Extensive experience with neural networks, including ...

office. You will act as the team lead and play a key role in building mission-critical financial applications that power trading, investment, and risk management systems across the firm. If you are passionate about working in a dynamic, fast-paced environment and are eager to apply your technical … Responsibilities: Design, develop, and maintain high-performance Back End services using GoLang to support financial applications and services , including trading platforms, investment systems, and risk management tools. Build and deploy cloud-based solutions using Amazon Web Services (AWS), including services such as EC2, S3, RDS, DynamoDB, and Lambda ...