Our Collections department is expanding its use of machine learning to optimize debt recovery, customer engagement, and operational efficiency. We're looking for a hands-on specialist to design, implement, and maintain production-ready ML models, while building the practices and infrastructure needed for sustainable, scalable use. This role is ideal for someone who thrives on applied, production-focused work and wants to shape how ML drives real impact in Collections from day one.
Challenges that await you
Develop and deploy production-ready ML models for segmentation, outreach optimization, and risk prediction.
Build and maintain data pipelines for model training, retraining, and monitoring.
Collaborate with engineers to integrate models into automated workflows and decision systems.
Define and implement best practices for ML in production (versioning, testing, monitoring).
Translate business problems into data-driven solutions and communicate results clearly to stakeholders.
What makes you a great fit
2+ years of hands-on experience in applied ML with a strong focus on classic algorithms (e.g., gradient boosting, decision trees, logistic regression).
Proficiency in Python and ML libraries such as scikit-learn, XGBoost, LightGBM.
