Build industry-leading machine learning models for managing credit and fraud risks
Leverage multiple complex data sources such as credit bureau reports and customer supplied information at large scale to optimize approve/decline and credit line assignment decisions
Propose and execute solutions to various problems within business constraints
Building, maintaining and enhancing credit risk models for lending portfolios.
Extract, clean and manipulate large data sets using SQL and Python; build pipelines and analytics to perform model and portfolio monitoring.
Perform exploratory data analysis (EDA) to identify portfolio trends, drivers of loss performance and provide insight into model deviations.
Achieve is a digital personal finance company that provides personalized financial solutions. They leverage data and analytics to offer personal loans, home equity loans, debt consolidation, and financial tools. They have over 3,000 employees and a strong people-first culture.
Build, lead, and mentor a machine learning engineering team, taking a hands-on approach while assuming increasing management responsibilities as the team grows
Design, develop, and deploy machine learning models to strengthen risk management and fraud detection capabilities
Own technical direction within the risk and fraud domain, helping define strategy, architecture, and best practices
Jobgether is a company that uses an AI-powered matching process to ensure applications are reviewed quickly, objectively, and fairly against the role's core requirements. They identify the top-fitting candidates, and this shortlist is then shared directly with the hiring company.
Contribute to the ML Roadmap : Identify and prioritize AI/ML opportunities across key areas such as credit risk, fraud detection, customer acquisition, and churn prevention
Prototype & Scale : Design, build, and deploy ML models that brings value to HALA, starting with rapid prototyping and scaling up based on impact
Data Strategy : Collaborate with engineering, product, and business teams to improve data collection practices and ensure we’re capturing the right signals for modeling
HALA is a leading fintech player in the MENAP region that aims to redefine financial services and build the future bank of SMEs. Founded in 2017, HALA has a diverse culture that encourages innovation and flexibility.
Leverage advanced data analytics to derive insights and optimise credit strategies across products and geographies.
Partner with Engineering to design and build scalable risk models and credit risk capabilities.
Collaborate closely with Product, Legal, and Compliance teams to interpret evolving regulatory and market requirements across jurisdictions, and translate them into credit policy, underwriting, and product design recommendations.
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. They are a fast-growing FinTech company committed to redefining responsible consumer lending.
Evaluate traditional, alternative, transactional, and raw datasets for use in underwriting, portfolio management, collections, and fraud.
Lead quantitative due diligence for M&A targets and data partnerships, assessing data quality, depth, coverage, stability, and scalability.
Design and implement validation frameworks to measure predictive lift, segmentation value, and incremental performance versus incumbent data.
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 and corporate headquarters are in Dublin, Ireland.
Support design and monitoring of EWA underwriting strategies and forecasting tools.
Query, clean, and analyze large bank transaction datasets using SQL and Python, or R/SAS).
Partner with Product, Engineering, Data Science, and Operations to implement updates to policies and decisioning logic.
Self Financial is a venture-backed, high-growth FinTech company with a mission to increase economic inclusion and financial resilience by empowering people to build credit and build savings. Their team is passionate about challenging the status quo of the credit industry by providing people accessible tools to take control of their credit.
This role is pivotal in building and scaling a team responsible for pricing, credit limit modelling, and production credit model deployment. You’ll work closely with our Consumer Credit, Product, and Engineering teams to shape how we assess and price risk, design credit products, and measure outcomes across the credit lifecycle. You’ll build the analytics and modelling foundations that inform underwriting, customer acquisition, retention, and portfolio performance at scale.
Moniepoint is a global fintech building modern financial services for millions of people and businesses across high-growth markets.
Engineer and validate consumer-level attributes from credit bureau and alternative data sources.
Apply statistical techniques to uncover insights and improve predictiveness.
Monitor attribute performance for stability, compliance, and accuracy.
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, investing in people and new advanced technologies to unlock the power of data.
Design and evaluate strategies to reduce fraud and abuse across promotions, referrals, refunds, and payment flows.
Develop and improve machine learning models, rules-based systems, and heuristics to detect high-risk behavior while minimizing false positives.
Analyze experimental and observational data using A/B testing and causal inference to measure the effectiveness of interventions in payments and fraud prevention.
Lime is the largest global shared micromobility business. Their electric bikes and scooters have powered more than one billion rides in cities around the world.
Identify and propose ML opportunities related to your scope and beyond
Conduct Exploratory Data Analysis and subsequent Feature Selection / Engineering
Deploy and test ML applications using our MLOps infrastructure
Yassir is the Super App designed to make your life easier. Yassir’s Mission is to serve Africans in the continent and its diaspora while creating economic opportunities for service providers and infusing social values. They are growing fast and are one of the most impactful, fastest-growing Tech companies in Africa.
Monitor applications, transactions, and customer activity to detect and prevent fraud and identity risks.
Apply machine learning models and statistical techniques to enhance fraud detection and prevention capabilities.
Partner with Operations, Credit, Technology and Compliance to align fraud strategies with enterprise objectives
Braviant Holdings is a tech-enabled credit products provider that combines technology and machine learning to transform how people access credit online. They are a privately held company based in Chicago, and have been named multiple times to the Inc. 5000 list and recognized as a Best Place to Work.
Be the day‑to‑day analytics partner for clients on credit strategy, risk optimization, and portfolio performance.
Translate client goals into clear analytical questions, project plans, and structured workflows.
Use Python and SQL to explore data, validate hypotheses, and support analytical workflows developed by Data Science teams.
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.
Partner with stakeholders to translate business challenges into data science problems.
Own the end-to-end lifecycle of data science models, from data exploration to deployment.
Develop scalable and efficient models, balancing algorithmic complexity with business needs.
Ocrolus helps lenders automate workflows with confidence, streamlining how financial institutions evaluate borrowers and enabling faster, more accurate lending decisions.
Improving portfolio health by engaging customers in financial difficulty.
Designing and monitoring impact assessment and forecasting models.
Developing and maintaining credit models for strategic business decisions.
Monzo is on a mission to make money work for everyone, waving goodbye to complicated traditional banking. They offer personal and business bank accounts, joint accounts, and credit cards, solving problems and changing lives.
We are seeking a highly skilled and motivated Senior Data Scientist to join a dynamic, data-driven team. Work on designing, building, and enhancing AI-powered analytics solutions that transform how organizations manage financial risk and optimize spend. Collaborate closely with product managers, engineers, and fellow data scientists to deliver machine learning models and analytical tools that have a direct impact on business outcomes.
Jobgether is a company that uses AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements.
Suggest and analyze Lifecycle Marketing campaigns rooted in clients’ delight and friction.
Employ and exemplify rigor in mathematical analyses and sound design principles in software development.
Collaborate with the Lifecycle Marketing team to define quarterly and yearly initiatives.
Wealthfront is a company that leverages technology to build powerful, low-cost, and easy-to-use financial products. They aim to help modern investors grow and manage their money and have over 1 million clients and $85 billion of their hard earned savings.
Manage our thought leadership strategy, grounded in data analysis and empirical thoughtfulness.
Use Python and SQL to independently explore datasets, validate hypotheses, and surface unique insights.
Translate analytical findings, model outputs, and product capabilities into clear, market‑facing narratives that demonstrate value.
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 and their corporate headquarters are in Dublin, Ireland.
Transform data into actionable insights for product, operational, and business decisions. Analyze complex datasets and build predictive models to solve ambiguous problems. Collaborate with cross-functional teams to define data needs and drive data-driven solutions.
Oowlish is one of Latin America's rapidly expanding software development companies.