Senior Data Scientist (Fraud)

Moniepoint

Who we are Ranked in 2024 by the Financial Times, Moniepoint is Africa’s fastest-growing fintech, trusted by over 10 million business and individual accounts, processing billions of Naira in transactions monthly. Our mission is to enable financial happiness for every African, everywhere. About the role:  We're looking for a Data Scientist to sit at the heart of how we fight fraud, building the models, experiments, and detection systems that protect millions of customers and merchants across our platform. This is a high-impact role at the intersection of machine learning, product, and engineering, where your work will directly shape how Moniepoint detects and responds to emerging fraud threats.  We are looking for a data-driven, intellectually curious Data Scientist who is energised by hard problems in fraud and financial crime. You'll prototype and ship ML models, design experiments, and uncover new fraud signals across our ecosystem, partnering closely with engineers, product managers, and analysts to turn your work into production-grade systems.  Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth. What You’ll Do * Model Development: Prototype, evaluate, and help productionize machine learning models for fraud detection; own their ongoing monitoring and retraining cycles.   * Experimentation: Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction.   * Risk Assessment: Size fraud typologies across our product lines to inform prioritisation and investment decisions.   * System Maintenance: Build and maintain anomaly detection systems to surface novel fraud vectors before they scale.   * Cross-Functional Collaboration: Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into real-world mitigations. We would love to hear from you if… * A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar) * 5+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime * Hands-on experience building and deploying machine learning models in a production environment, fraud, risk, or financial services experience is a strong plus * Solid grounding in data science fundamentals: experimentation, statistical inference, model evaluation, and feature engineering * Proficiency in Python and SQL; comfort working across the full model development lifecycle * An investigative instinct, you enjoy digging into data to find patterns others miss * The ability to communicate technical findings clearly to non-technical stakeholders and translate insights into action * Comfort working in fast-paced, cross-functional teams with high ownership expectations What we can offer you * Culture: We put our people first and prioritise the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human. * Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks. * Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits What to expect in the hiring process * A preliminary phone call with the recruiter * An interview with a business lead * Technical take-home task (SQL/Python test and case study) * A behavioural and technical interview with the Head of Data Science and a member of the executive team Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

Moniepoint

Who we are Ranked in 2024 by the Financial Times, Moniepoint is Africa’s fastest-growing fintech, trusted by over 10 million business and individual accounts, processing billions of Naira in transactions monthly. Our mission is to enable financial happiness for every African, everywhere. About the role:  We're looking for a Data Scientist to sit at the heart of how we fight fraud, building the models, experiments, and detection systems that protect millions of customers and merchants across our platform. This is a high-impact role at the intersection of machine learning, product, and engineering, where your work will directly shape how Moniepoint detects and responds to emerging fraud threats.  We are looking for a data-driven, intellectually curious Data Scientist who is energised by hard problems in fraud and financial crime. You'll prototype and ship ML models, design experiments, and uncover new fraud signals across our ecosystem, partnering closely with engineers, product managers, and analysts to turn your work into production-grade systems.  Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth. What You’ll Do * Model Development: Prototype, evaluate, and help productionize machine learning models for fraud detection; own their ongoing monitoring and retraining cycles.   * Experimentation: Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction.   * Risk Assessment: Size fraud typologies across our product lines to inform prioritisation and investment decisions.   * System Maintenance: Build and maintain anomaly detection systems to surface novel fraud vectors before they scale.   * Cross-Functional Collaboration: Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into real-world mitigations. We would love to hear from you if… * A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar) * 5+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime * Hands-on experience building and deploying machine learning models in a production environment, fraud, risk, or financial services experience is a strong plus * Solid grounding in data science fundamentals: experimentation, statistical inference, model evaluation, and feature engineering * Proficiency in Python and SQL; comfort working across the full model development lifecycle * An investigative instinct, you enjoy digging into data to find patterns others miss * The ability to communicate technical findings clearly to non-technical stakeholders and translate insights into action * Comfort working in fast-paced, cross-functional teams with high ownership expectations What we can offer you * Culture: We put our people first and prioritise the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human. * Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks. * Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits What to expect in the hiring process * A preliminary phone call with the recruiter * An interview with a business lead * Technical take-home task (SQL/Python test and case study) * A behavioural and technical interview with the Head of Data Science and a member of the executive team Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

AB InBev

About us AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa. About AB InBev Growth Group Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world. In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and TaDa Delivery, and table top beer keg PerfectDraft. We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities.   About BEES BEES, our ambition is – and always will be – to put customers at the heart of everything we do. Making their lives easier and their businesses more profitable. Through our B2B e-commerce and SaaS platform, we bring the power of digital to small and medium-sized retailers and the companies that service them, unlocking new growth opportunities for all. With offices in São Paulo and Campinas, we encourage our team to participate in major events and significant meetings throughout the year. The Team: BEES is the team driving AI strategy at BEES by building end-to-end products to serve our teams, customers, and partners across the globe. The organization is a cross-functional blend of AI/ML teams from Applied Research and Machine Learning Engineering to Machine Learning Platform Product Management. Together, the team is responsible for building the tools and products needed to deliver world-class AI/ML capabilities.  As a member of the BEES Fintech Data Science team, you will develop data-driven solutions for credit risk, underwriting, portfolio optimization, pricing, and decisioning systems that operate at scale and directly impact real-time credit decisions. What you'll do: * Be part of a high-impact fintech data science team building ABIs credit models, credit decisioning systems, and ML-powered infrastructure that drive billions of dollars in credit transactions annually for millions of users worldwide. * Design, develop, and deploy statistical and machine learning models across the full lifecycle — from research and experimentation to production — with a focus on credit risk, underwriting, portfolio optimization, and experimentation. * Write a substantial amount of production-grade code while conducting deep analytical and statistical research, translating theory into practical improvements in live credit systems. * Lead and contribute to experimentation and model evaluation (offline analysis, simulations, and online tests), ensuring models are robust, explainable, and aligned with regulatory, risk, and business constraints. * Work with industry-leading technologies and modern ML platforms, building scalable modeling and data workflows that operate reliably at global scale. * Collaborate closely with exceptional engineers, product managers, analysts, and business stakeholders. * Continuously explore and adopt state-of-the-art methods in statistics, machine learning, and optimization, raising the technical bar and shaping best practices across the fintech data science organization. What you'll need: * Strong foundation in mathematics and statistics. * Bachelor’s degree in Mathematics, Statistics, Engineering, Computer Science, or a related quantitative field; Master’s preferred; PhD a plus. * Experience or strong familiarity with experimentation frameworks, model validation, and rigorous evaluation, ideally in high-stakes decision systems. * Proven ability to apply machine learning and statistical models in production, balancing accuracy, stability, explainability, and real-world constraints. * Proficiency in Python for analysis, modeling, and production workflows; experience with distributed data processing (e.g., Spark / PySpark) is a plus. * Experience with modern ML development practices, including version control, CI/CD, and reproducible research and modeling workflows. * Strong proficiency using AI coding agents and developer tools in a controlled, thoughtful, and production-oriented way to accelerate development without compromising quality. * Creative, curious, and independent thinker who challenges assumptions, proposes novel approaches, and reasons deeply about complex systems. * Excellent communication skills, able to clearly explain complex models and results to both technical and non-technical audiences. What We Offer: * Performance based bonus* * Attendance Bonus*  * Private pension plan * Meal Allowance * Casual office and dress code * Days off* * Health, dental, and life insurance * Medicines discounts * WellHub partnership * Childcare subsidies * Discounts on Ambev products* * Clube Ben partnership * Scholarship* * School materials assurance * Language and training platforms * Transport allowance *Rules applied Equal Opportunity & Affirmative Action: AB InBev Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics. The following fields are optional, but anticipate the information for your registration*. Remember: your data will never be used as elimination criteria in selection processes. With them, AB InBev Growth Group is able to analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive company.  For more information: www.abinbev.com