Data Scientist – Alerting & Triage Optimization

Data Scientist – Alerting & Triage Optimization

Location: Toronto, ON (Hybrid)

Job Overview

We are seeking an experienced Data Scientist to design and optimize next-generation alerting and triage capabilities across fraud, security, and operational risk domains.

The role focuses on building data-driven solutions that improve detection accuracy, reduce alert noise, and enable efficient, scalable triage. You will help transform manual, reactive alert monitoring into proactive, AI-driven detection and triage , including real-time anomaly detection and multi-agent AI frameworks.

Key Responsibilities

• Design and optimize alerting thresholds and anomaly detection logic for large-scale monitoring systems.
• Analyze alert data to identify false positives, missed detections, and signal gaps and improve alert quality.
• Develop and apply machine learning models for anomaly detection, clustering, and pattern recognition.
• Enable GenAI-powered and agent-based workflows for automated alert analysis, enrichment, and triage recommendations.
• Translate analyst workflows into automated and scalable solutions to reduce manual investigation.
• Build and maintain data pipelines and analytical workflows in Databricks and enterprise data platforms.
• Define and track alert performance metrics such as precision, noise reduction, and escalation quality .
• Ensure models, thresholds, and outputs are explainable, traceable, and audit-ready .

Required Skills & Experience

• Strong experience in Data Science, Analytics, or Machine Learning .
• Proficiency in Python and SQL for data analysis and model development.
• Hands-on experience with Databricks or similar large-scale data platforms.
• Strong understanding of:
• Anomaly Detection
• Threshold Calibration
• Signal Optimization
• Model Performance Evaluation
• Experience working with alerting systems, monitoring data, or operational metrics .
• Ability to translate complex data into clear, actionable insights.