Source Job

• Analyze banking transactions and enhance fraud detection algorithms using graph-based analysis of financial data.
• Build and integrate ML models, including classic, graph-based, and neural network approaches, into the Fraud Protection platform.
• Document research findings and present them to stakeholders, contributing to broader graph-related tasks like GraphRAG components.

Group-IB is a leading cybersecurity technology creator dedicated to investigating, preventing, and fighting digital crime. With over 1,550 cybercrime investigations and 600+ enterprise customers globally, the company operates Digital Crime Resistance Centers across multiple regions, fostering a culture of mission-driven innovation and global collaboration.

• Lead a high-calibre ML team to shape Borrowing's ML roadmap across UK growth, new customer segments, and EU expansion.
• Improve underwriting, pricing, limits, and lifecycle decisioning through faster model iteration and new data sources.
• Partner with leaders across Credit Strategy, Product, Engineering, and Data to drive commercial impact and long-term strategic advantage.

Monzo is on a mission to make money work for everyone, offering personal and business bank accounts, savings, investments, and pensions. As a rapidly growing fintech with a strong UK presence, we foster an inclusive culture focused on innovation and customer delight.

• Design, develop and deploy advanced statistical or machine learning models for credit risk, pricing, collections, fraud, and other high-impact business use cases.
• Lead end-to-end delivery of data science initiatives from problem framing through deployment and monitoring.
• Partner with cross-functional teams including Portfolio Strategy, Engineering, Product, and Sales to integrate models and solve critical business problems.

Forward Financing is a fintech company that unlocks capital for small businesses across America. Since 2012, it has provided over $4.8 billion in funding to more than 92,000 small businesses and is recognized as a Best Place to Work by Built In Boston.

• Lead the ML strategy for Workforce Management, delivering production systems for forecasting, routing, and optimisation.
• Coach and develop a growing team of Machine Learning Scientists embedded in product squads.
• Work cross-functionally with Product, Engineering, Data, and Operations leaders to solve ambiguous operational problems.

Monzo is a digital bank on a mission to make money work for everyone, offering personal and business bank accounts, savings, investments, and pension consolidation. With over 10 years of growth in the UK and a focus on financial education and award-winning customer service, Monzo has a vibrant culture and a strong commitment to diversity and inclusion.

• Build and deploy machine learning models to detect and respond to fraud across the platform.
• Design experiments to measure the impact of fraud interventions, balancing customer experience and loss reduction.
• Collaborate with fraud operations, engineers, and product managers to translate model outputs into real-world mitigations.

Moniepoint is Africa's fastest-growing fintech, trusted by over 10 million business and individual accounts, processing billions in transactions monthly. They have a people-first culture focused on learning and inclusion, valuing diversity and employee well-being.

• Set the technical strategy for your team, tying together critical projects across repayment, collections, recovery, and loss mitigation.
• Act as a force-multiplier by defining and advocating technical solutions and operational processes.
• Collaborate with product management, design, analytics, and risk to ensure technical sustainability and manage trade-offs.

Affirm is reinventing credit to make it more honest and friendly, giving consumers flexibility to buy now and pay later without hidden fees. The company is remote-first with a focus on people-first culture and offers competitive benefits.

• Build and operate the real-time inference service for the risk decision engine with low latency and high availability.
• Own model deployment infrastructure including CI/CD, shadow mode, and staged rollouts.
• Build model observability and partner with Risk Data Science for production operation.

Mercury is a fintech company that provides banking services for startups via partner banks. The company is committed to creating a safe environment and values diversity, with a growing team focused on innovation.

• Build and maintain backend services, Python libraries, and model lifecycle tooling for internal ML teams.
• Design and operate distributed systems for model serving, evaluation, and feature engineering.
• Focus on developer experience and reliability to help teams train, deploy, and serve ML models safely.

Monzo is on a mission to make money work for everyone, offering personal and business bank accounts, savings, investments, and more through a modern digital banking platform. With around 600 engineers out of roughly 5,000 employees, we value flexibility, collaboration, and open source contributions.

• Leading, coaching, and developing high-performing Financial Crime teams to create an environment for best work.
• Driving operational excellence across anti-money laundering and financial crime processes to ensure quality and efficiency.
• Collaborating with risk, product, and operational stakeholders to deliver improvements and maintain a strong risk control environment.

Monzo is a digital bank on a mission to make money work for everyone, offering a range of innovative banking products from personal accounts to investments. With over 10 years in the UK, they foster an inclusive culture and provide a £1,000 learning budget for employees.

• Develop machine learning and AI solutions for forecasting, anomaly detection, and operational intelligence.
• Design scalable enterprise data architectures and build ETL/ELT pipelines for analytics and AI workloads.
• Partner with stakeholders to define metrics, lead technical reviews, and mentor team members.

DataDirect Networks (DDN) is a global market leader in AI and high-performance data storage innovation, powering many of the world's most demanding AI data centers across industries like life sciences, healthcare, financial services, and research. With a proven track record of performance and scalability, DDN fosters a culture of innovation, customer-centricity, and passionate professionals committed to excellence.

• Use SQL and other analytical tools to conduct in-depth analysis of customers, transactions, alerts, and risk ratings.
• Develop, tune, and maintain transaction monitoring and sanctions screening models to improve detection and reduce false positives.
• Partner with compliance, product, and data leaders to translate regulatory requirements into effective analytical frameworks.

Mercury is building a complete finance stack for startups, providing banking services through partner banks. As a fintech company, they focus on creating a safe and easy banking experience while protecting against bad actors, with a culture of high agency and adaptability.

• Serve as the designated Money Laundering Reporting Officer (SMF17) for the UK entity, overseeing the financial crimes compliance program.
• Lead the development of the Financial Crime Compliance Monitoring Programme and business-wide compliance risk assessment.
• Partner with UK Compliance and global Financial Crimes leaders to maintain a clear and effective control environment across onboarding, transaction monitoring, and investigations.

Affirm is reinventing credit to make it more honest and friendly, offering buy now pay later without hidden fees or compounding interest. It is a remote-first company with competitive benefits including full health coverage and stipends.

• Develop, validate, and optimize statistical and machine learning models including regression and XGBoost to detect and prevent fraud.
• Design features, build tools, and deploy models in production environments to improve performance and stability.
• Conduct model governance activities including validation, documentation, and ongoing monitoring with clear reporting.

Experian is a global data and technology company powering opportunities for people and businesses worldwide, operating across financial services, healthcare, automotive, and more. With 23,300 employees in 32 countries, the company is a FTSE 100 Index listed firm recognized for its people-first culture and advanced technology investments.

• Developing machine learning pipelines and custom analytics for image, video, text, geospatial, time series, and structured data
• Orchestrating and automating complex data engineering and analytic pipelines
• Envisioning, specifying, designing, and implementing core product functionality and conducting mission-critical fieldwork

Striveworks helps organizations harness AI to solve national security and business challenges by serving as a command center between data, models, and outcomes. Founded by data scientists and engineers, the company values a high-trust work environment with individual responsibility for collective results.

• Design, train, and evaluate machine learning models to address business problems.
• Build and maintain data pipelines and infrastructure for model development and deployment.
• Deploy ML models into production and monitor performance, reliability, and drift.

Critical Software delivers software solutions and consulting in complex, business-critical environments across industries like aerospace, defense, and healthcare. They are a Benefit Corporation committed to positive impact and an equal opportunity employer.

• Design and operate core AI platform components for training, deploying, and serving ML models at scale.
• Own model serving and inference workflows end-to-end, optimizing for reliability, latency, throughput, and cost.
• Collaborate with product, infrastructure, and security teams to build scalable platform capabilities for AI-powered features.

Mozilla Corporation is the non-profit-backed technology company behind Firefox and Pocket, with over 225 million monthly users. A wholly-owned subsidiary of the Mozilla Foundation, the company is mission-driven, employee-owned, and focused on privacy and open standards.