Data Scientist - Level 9

Procom; Toronto; Hybrid; CAD 110,000 - 150,000; Full time

Job summary

Procom is seeking a Data Scientist at Level 9 for a 6-month hybrid position based in Toronto, ON. The role focuses on designing and optimizing alerting and triage capabilities across fraud, security, and operational risk, with an emphasis on scalable, data-driven solutions.

You'll build data pipelines in Databricks, develop ML models to detect anomalies, and enable GenAI-powered workflows for automated alert analysis. Strong Python/SQL skills and knowledge of anomaly detection are essential.

Qualifications

• 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 and large-scale data platforms.

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 implement improvements.
• Develop machine learning models to detect abnormal behavior across datasets.
• Enable GenAI-powered workflows to automate alert analysis and triage recommendations.
• Translate analyst workflows into automated, scalable solutions.
• Build and maintain data pipelines and analytical workflows in Databricks.
• Define and track alert performance metrics to improve signal effectiveness.
• Ensure all models and outputs are explainable and audit-ready.

Skills

Data science

Python

SQL

Databricks

Anomaly detection

Alerting systems

GenAI concepts

Data storytelling

Tools

Databricks

Power BI

Splunk

Datadog

TMX

BioCatch

Job description

Data Scientist - Level 9:

On behalf of our Banking client, Procom is searching for a Data Scientist - Level 9 for a 6-month role. This position is a hybrid position with 3 days onsite at our client's Toronto, ON office.

Data Scientist - Level 9 - Job Description:

We are seeking a Data Scientist to design and optimize next-generation alerting and triage capabilities across fraud, security, and operational risk domains. This role focuses on advancing alerting and automation capabilities by building data-driven systems that improve detection accuracy and enable efficient, scalable triage.

Data Scientist - Level 9 - 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 implement improvements.


• Develop machine learning models to detect abnormal behavior across datasets.


• Enable GenAI-powered workflows to automate alert analysis and triage recommendations.


• Translate analyst workflows into automated, scalable solutions.


• Build and maintain data pipelines and analytical workflows in Databricks.


• Define and track alert performance metrics to improve signal effectiveness.


• Ensure all models and outputs are explainable and audit-ready.

Data Scientist - Level 9 - Mandatory Skills:

• 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 and large-scale data platforms.


• Solid understanding of anomaly detection techniques.


• Experience working with alerting systems or operational metrics.


• Ability to translate complex data into clear, actionable insights.


• Understanding of AI/GenAI concepts and agent-based architectures.

Data Scientist - Level 9 - Nice-to-Have Skills:

• Experience with Power BI or similar visualization tools.


• Exposure to Splunk, Datadog, TMX, BioCatch, or similar alerting platforms.


• Experience in fraud, cybersecurity, or operational risk analytics.


• Experience working in regulated or audit-driven environments.


• Experience with GenAI or agentic AI workflows.

Data Scientist - Level 9 - Assignment Length:

This is a 6-month contract position, extendable.

Data Scientist - Level 9 - Start Date:

ASAP.

Data Scientist - Level 9 - Assignment Location:

Toronto, ON, Canada (Hybrid) - 3 days/week in-office.