Job description
This is a remote position.
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
You are a good fit if you have:
An MS 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 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
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.