Source Job

• 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.

• Own the full lifecycle of statistical and machine learning model development, from data exploration to deployment.
• Improve efficiency in credit risk, fraud, marketing, and collections by deploying modeling solutions.
• Research and develop new methods and tools to improve the business and present results to leadership.

Attain Finance is a consumer credit lender with over 50 years of expertise providing credit solutions across the U.S. and Canada. The company is a leading lender with a dynamic, collaborative culture and a portfolio of distinguished brands.

• Develop credit and fraud strategies using data, machine learning models, and advanced analytics to optimize risk decisions.
• Design A/B tests to balance risk and customer experience, and partner with Data Science, Product, and Engineering teams.
• Analyze portfolio performance at a granular level, identify trends, and communicate findings to Risk Management.

Prosper is a fintech company that pioneered peer-to-peer lending in the US, offering personal loans and credit cards to help consumers achieve financial well-being. Since 2005, it has served over 2 million customers and fosters a culture of collaboration, curiosity, and accountability.

• 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.

• You will leverage advanced ML models to detect suspicious user behaviors while minimizing impact on genuine customers.
• You will adapt quickly to changing fraud trends to keep detection systems performant over time.
• You will design machine learning solutions that scale globally.

We're on a mission to make money work for everyone, offering personal and business bank accounts, savings, investments, and more. We've grown significantly in the UK over the last 10 years and have a strong culture of innovation and customer focus.

• 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.

• Partner with business leaders to identify opportunities and develop analytical strategies.
• Create predictive models and scalable machine learning solutions to optimize customer acquisition and retention.
• Translate complex data findings into clear business recommendations and drive experimentation.

This company leverages advanced data science and machine learning to solve complex business challenges. It fosters a collaborative and inclusive culture focused on innovation, growth, and teamwork.

• Collaborate with business leaders to translate high-impact business problems into data science and data analysis projects.
• Develop and implement predictive models and machine learning algorithms for forecasting, customer segmentation, and optimization.
• Perform exploratory data analysis and create compelling dashboards and reports for both technical and non-technical audiences.

Concurrent Technologies Corporation is an independent, nonprofit applied scientific research and development organization. It fosters a collaborative, customer-focused environment where technology enables engineers, researchers, and business professionals to accomplish their mission.

• 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.

• Build advanced machine learning models to detect and prevent financial crime, reducing fraud and scams.
• Work cross-functionally with product managers, data scientists, and engineers in an agile environment.
• Provide technical leadership and mentorship to drive up standards in machine learning practices.

Monzo is on a mission to make money work for everyone by offering personal and business bank accounts, savings, investments, and credit cards in the UK. With over 25 people in the Financial Crime Data team, we foster a culture of innovation and inclusivity.

• Develop production-ready analytics that support smarter energy decisions, improve grid reliability, and accelerate the transition toward a more sustainable future.
• Lead the design, development, and refinement of statistical and machine learning models for load forecasting, flexibility analysis, customer behavior modeling, and energy resource optimization.
• Analyze large-scale datasets including smart meter data, customer information, grid attributes, and external factors to identify patterns and support strategic decision-making.

Our partner company offers the opportunity to apply advanced data science, machine learning, and AI techniques to solve complex challenges in the energy sector. You will work with one of the largest energy datasets available, combining large-scale meter data, weather information, geospatial context, and grid attributes.

• Build and ship ML models to help customers search and find answers about their financial lives.
• Develop user and product embeddings, contextual bandits, and personalized ranking algorithms.
• Work with a modern cloud-native data platform to deploy models to millions of customers.

Monzo is on a mission to make money work for everyone, offering personal and business bank accounts, savings, investments, and pensions with a focus on solving problems and changing lives. With over 15 million customers and a culture of innovation, Monzo prioritizes diversity and inclusion.

• Lead the design and execution of data science projects, ensuring high-impact analytics solutions.
• Partner with client stakeholders to develop data-driven strategies and present findings to executives.
• Mentor team members and influence data governance and best practices within the organization.

Excella is a transformative technology firm that helps organizations unlock new possibilities. They are committed to developing talent and providing opportunities for career growth at every stage, with a collaborative team dedicated to solving complex problems.

• Identify and own challenging problems, form testable hypotheses, and drive significant business impact.
• Lead the design and analysis of experiments or development of causal and predictive models to test your ideas.
• Collaborate with product and engineering to affect changes in production systems and provide intelligence to other teams.

Yelp operates a platform connecting users with local businesses through user-contributed content. As a large company with millions of users and listings, it fosters a cooperative culture that values individual authenticity and encourages creative solutions.

• 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.

• Build and maintain data pipelines for analytics, ML, and product applications.
• Design scalable data infrastructure with a focus on quality and observability.
• Collaborate with cross-functional teams to understand data needs and implement solutions.

Prolific builds human data infrastructure to power the next wave of AI innovation. They are a remote-first company focused on ethical data collection and mission-driven culture.

• Design and execute structured evaluation frameworks to assess the quality and fraud-signal value of incoming data assets from vendor partners.
• Build lift analyses, backtests, and champion/challenger comparisons to quantify the incremental value of new data signals against our existing fraud detection stack.
• Collaborate with fraud leadership to define evaluation criteria and translate vendor data findings into actionable recommendations such as adopt, pilot, or decline.

Sardine is the leading agentic risk platform for fighting financial crime, unifying data across risk teams to stop fraud in real time and prevent AI-driven attacks. They are a remote-first company with hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo, valuing performance and self-motivated individuals.

• Define the technical strategy and roadmap for credit risk and fraud detection using statistical and ML approaches.
• Design, build, and deploy production-quality machine learning models for credit scoring, fraud detection, and risk modeling.
• Collaborate closely with Engineering, Product, Risk, and Operations teams to align data science strategy with business goals.

Djamo builds the future of banking in Africa with a super-app that combines payments, transfers, savings, and budgeting. Launched in 2020, the company serves over one million users and is backed by investors like Y Combinator and Partech, fostering a culture of innovation and inclusion.

• Work collaboratively with HCD lead to analyze data, form insights and predictions for CMS price transparency initiatives.
• Build predictive models, AI tools, and data visualizations to support product design and automate processes.
• Perform data mining, feature selection, and anomaly detection using machine learning techniques in an agile environment.

Bellese is a mission-driven digital services company pioneering innovative technology solutions in civic healthcare. It fosters a collaborative, remote-first culture and invests in employee well-being with comprehensive benefits.

• Design robust feature representations from implicit behavioral data to capture true user intent.
• Architect sequential models that adapt to shifting user preferences for personalized recommendations.
• Integrate ML scores with operations-research engines to balance personalization with business constraints.

Hungryroot uses AI to build a consumer-centric food and wellness company, acting as a personal assistant for healthy living. They are a distributed team of top talent across 28+ U.S. states with a remote-first culture emphasizing collaboration and flexibility.