Remote Senior ML Engineer

Description:

• Owns predictive customer scores including churn, propensity, lifetime value, spend intent, and response scoring.
• Applies machine learning and tabular predictive modeling to customer data, managing production models.
• Works across the full model lifecycle: training, deployment, retraining, monitoring, evaluation, and calibration.
• Supports predictive use cases with a focus on models running in production.

Requirements:

• Experience with applied machine learning models in production environments.
• Deep expertise in tabular predictive modeling on customer data.
• Proven experience building churn or propensity models in telco, banking, or retail sectors.
• Familiarity with training, deployment, and retraining pipelines in a self-managed environment.
• Knowledge of MLOps practices including model registry, versioning, retraining, monitoring, and drift detection.
• Comfortable working within a data platform rather than using notebooks.
• Experience with uplift or causal modeling for incremental targeting.
• Understanding of feature store design.
• Ability to collaborate with commercial stakeholders on prediction applications.

Benefits:

• Opportunity to work on impactful predictive modeling projects.
• Engage with cross-functional teams and commercial stakeholders.