Migo
51 - 200 employees
Founded 2014
💳 Fintech
🔌 API
🤝 B2B
💰 $20M Series B - Migo on 2019-12
Fintech • API • B2B
Migo is a fintech company that provides embedded microlending and consumer credit services via a simple API and cloud infrastructure. It offers fast, no-collateral personal and salary loans (notably in Nigeria) with quick approvals and uses machine learning to assess credit risk and reduce defaults. Migo partners with banks, merchants, fintechs and telcos to enable credit products, increase sales and reach underserved or unbanked customers.
Principal Data Scientist
Job not on LinkedIn
🕒 August 14, 2025
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Migo
51 - 200 employees
Founded 2014
💳 Fintech
🔌 API
🤝 B2B
💰 $20M Series B - Migo on 2019-12
Fintech • API • B2B
Migo is a fintech company that provides embedded microlending and consumer credit services via a simple API and cloud infrastructure. It offers fast, no-collateral personal and salary loans (notably in Nigeria) with quick approvals and uses machine learning to assess credit risk and reduce defaults. Migo partners with banks, merchants, fintechs and telcos to enable credit products, increase sales and reach underserved or unbanked customers.
📋 Description
• Take full ownership of credit risk modelling strategy • Design and develop credit scoring, underwriting, and forecasting models • Manage end-to-end ML pipelines • Research and implement modelling techniques • Ensure robust feature engineering, performance evaluation, and scalable deployment • Drive lending decisions and financial performance forecasting • Collaborate with cross-functional teams for market strategies • Maintain data integrity and model governance
🎯 Requirements
• A PhD in Computer Science, Statistics, Economics, Physics, or equivalent experience • Experience developing new modeling approaches, incorporating and adapting the latest methods in the field • Experience developing ETL and feature engineering data pipeline • Deep understanding of inductive biases of methods in ML and statistics • Deep understanding of metrics and appropriate model performance measurement • Ability to generalize product applications to new markets and partnerships • Strong understanding of and experience with causal inference concepts such as positivity assumption, confounding, and exchangeability • Deep understanding of ML and statistical concepts such as regularization, prediction vs. inference, multiple testing, cross-validation, boosting/bagging • Experience with a variety of ML methods, especially those for tabular data and in the lending/finance space • Experience with Python and object-oriented programming, developing and deploying production models, and contributing to shared, reusable libraries • Experience with A/B testing • Full proficiency in SQL
🏖️ Benefits
• Competitive salary • Health insurance • Paid time off • Flexible work arrangements • Professional development opportunities
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