Fresh Jobs at Migo Money Inc

About the Role

• As the Principal Data Scientist at Migo, you will take full ownership of our credit risk modelling strategy, from the design and development of credit scoring, underwriting, and forecasting models to the end-to-end management of ML pipelines.
• You will research and implement cutting-edge modelling techniques, ensuring robust feature engineering, rigorous performance evaluation, and scalable deployment into production.
• Your work will directly drive lending decisions, financial performance forecasting, and market expansion strategies.
• Collaborating with cross-functional teams, you will generalise solutions for new markets, apply causal inference and statistical best practices, and maintain high standards in data integrity and model governance, helping Migo deliver responsible and data-driven financial products across Nigeria and beyond.

Responsibilities

• Full ownership of ML models and credit risk modeling methodology
  • Credit scoring models (probability of default, survival analysis models)
  • Underwriting models (credit line assignment and risk assessment models)
  • Forecasting models (projected financial contribution and performance metrics)
• Ownership of ML pipelines and workflows (ETL, data preprocessing, feature engineering, model training, model deployment)

Requirements
You are a good fit if you have:

• 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

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Job Description

• As a Senior Data Scientist at Migo, you will play a key role in optimising our machine learning-driven decision systems, from monitoring and retraining existing models to developing new ones that power automated lending decisions.
• You will analyse performance data to refine features, select optimal models for different customer segments, and integrate new data sources into our modelling frameworks.
• Your work will combine statistical rigour with practical problem-solving, leveraging causal inference concepts, A/B testing, and robust ETL pipelines to improve model accuracy and stability.
• Working closely with engineering and product teams, you will ensure our decision-making systems remain adaptable, data-driven, and effective as we scale into new markets and serve a growing customer base.

Responsibilities

• Analyze business data to assess performance and identify areas for improvement
• Monitor, retrain, and iteratively improve machine learning models
• Add and remove features based on performance analysis
• Select optimal models for different customer segments using established metrics
• Integrate new data sources into existing modeling frameworks
• Analyze new data to develop rule-based and heuristic approaches
• Monitor and develop ETL and feature engineering pipelines
• Develop new ML models for automated decision-making

Requirements

• An MSc in Machine Learning, Data Science, Economics, or (Applied) Statistics, or equivalent experience
• Experience with ML lifecycle and statistical modeling
• Knowledge of ML concepts such as model drift and data leakage
• Experience developing new machine learning models
• Familiarity with the basics of causal inference
• Experience with Python and object-oriented programming
• Experience in data pipelines and ETL processes
• Experience with A/B testing
• Full proficiency in SQL.