Develop and iterate on fraud prediction models using a mix of approaches for tabular and behavioral data.
Build and scale feature pipelines and training datasets from proprietary and third-party signals.
Prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
Expand ML Capabilities – Identify, prototype, and integrate new ML technologies and infrastructure to enhance fraud detection effectiveness and scalability.
Enable High-Velocity Experimentation – Own the design and implementation of ML pipeline components that accelerate our innovation
Collaborate Across Functions – Partner with Product, Engineering, and Risk teams to translate business requirements into technical solutions and ensure ML initiatives align with customer needs.
Signifyd helps merchants confidently grow their businesses by building trusted relationships with their customers. Thousands of leading merchants across more than 100 countries trust them and they securely process billions of transactions each year. Their people are the heart of everything they do, driving their mission forward with commitment, empathy, and creativity.
Design, build, and iterate on machine learning models and LLM-based systems that power critical decisions across fraud, compliance, growth, and operations
Work with messy, real-world data to identify signals, build features, and continuously improve model performance
Make practical tradeoffs between model performance, interpretability, and operational cost
River is building the world’s most trusted financial institution to empower people to take ownership of their financial lives through Bitcoin. River is growing quickly and has raised more than $50 million from leading investors.
Lead data-driven product strategy initiatives supporting fraud detection and prevention systems
Design and deliver insights, reporting, and analytical frameworks to detect and mitigate fraud at scale
Define, track, and evaluate key metrics, including machine learning model performance and business impact
Maleda Tech is focused on protecting platform integrity by embedding measurement, experimentation, and insights into product defenses and user journeys. They are a global technology environment with a fraud & safety analytics team.
Own and operate machine learning models that run in production, including monitoring, debugging, and iterative improvement.
Develop, train, and optimize models used in a real-time or near-real-time bidding and decisioning system.
Work with stakeholders to clarify ambiguous problems, define success metrics, and translate business needs into technical solutions.
Healthcare.com is a fast-growing insurtech company revolutionizing how consumers shop for health insurance. They leverage advanced technology and data science, developing customized proprietary products to better fit consumer requirements and enhance customer satisfaction.
Improve customer and business outcomes through better automated decisioning, using Machine Learning and statistical modelling.
Drive innovations by identifying new opportunities of data and ML applications, and delivering business values across multiple Borrowing products.
Champion the quality and efficiency of model development, and ensure safe and scalable growth of their model portfolio.
Monzo is on a mission to make money work for everyone. They're waving goodbye to the complicated and confusing ways of traditional banking and want to solve problems and change lives through Monzo. The company cares deeply about their 15+ million customers.
Create advanced machine learning analytical solutions to extract insights from diverse structured and unstructured data sources.
Unearth data value by selecting and applying the right machine learning, deep learning and processing techniques.
Refine data manipulation and retrieval through the design of efficient data structures and storage solutions.
Experian is a global data and technology company, powering opportunities for people and businesses around the world. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), they have a team of 22,500 people across 32 countries that invests in people and new advanced technologies to unlock the power of data.
Design, develop, and enhance ML/AI models which mainly power Search and Recommendation.
Process historical data, search queries, product catalog, and images to extract hidden relations and features.
Work closely with Data Engineers and Senior Data Scientists to integrate and scale ML components to a production-level that can handle terabytes of data.
Bloomreach is building the world’s premier agentic platform for personalization, revolutionizing how businesses connect with their customers. They power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora.