We’re looking for a data-savvy analyst with strong SQL skills, curiosity, and the ability to interpret what data is really saying. You should enjoy working with complex datasets, noticing patterns and anomalies, and understanding what drives changes in the numbers.

Your main focus will be to strengthen our monitoring framework - designing, refining, and maintaining dashboards and alert systems that track how models and features behave in production. Beyond reporting, you’ll own the alert response process: investigating anomalies, identifying root causes, and working with other teams to drive meaningful improvements that impact business decisions.

Responsibilities:

• Build and maintain SQL-based dashboards for tracking model stability, data drift, and feature quality.

• Strengthen the monitoring system by designing and refining alert logic.

• Investigate triggered alerts, analyze root causes, and propose corrective actions.

• Monitor data consistency across sources and time periods.

• Support model documentation and periodic validation reports.

What we expect from candidate:

• Strong SQL expertise and experience working with large, complex datasets.

• Experience in data validation, monitoring, or analytical quality control.

• Basic Python for data analysis and automation; experience in model development would be a plus.

• Solid understanding of data distributions, metrics, and statistical reasoning - ability to interpret what data trends mean.

• High attention to detail, initiative, and ability to work independently.

Would be a big plus:

• Experience with Databricks or dbt.

• Familiarity with model monitoring concepts or credit scoring systems.

• Background in statistics, experimentation, or A/B analysis.

This is a chance to strengthen and expand the monitoring system that directly supports key credit decisioning models and drives measurable business impact.