Staff Data Scientist — AI Security & Anomaly Detection

Ultimate.ai; Montreal (administrative region); Hybrid; CAD 120,000 - 180,000; Full time

Job summary

Zendesk is seeking a Staff Data Scientist to join the AI Security team to envision and develop ML approaches that identify anomalous activity and AI security risks. You will collaborate with Security Engineers, Software Engineers, ML researchers, and product teams to share actionable insights and models for keeping customers safe and preventing product abuse.

Responsibilities include building an evaluation platform, analyzing large-scale data, and mentoring others while staying ahead of AI

Qualifications

• Advanced degree or equivalent practical experience in a quantitative field.
• 5+ years applying ML/AI in fraud detection, anomaly detection, or security.
• Strong SQL and Python with data processing frameworks.
• Fluency with AI-assisted programming tools (Claude Code, Cursor AI).
• Experience with a variety of statistical, ML, data mining and time-series techniques.

Responsibilities

• Develop and run the AI Security evaluation platform.
• Analyze large-scale behavioral data to identify abuse patterns.
• Develop detection models using offline data for production guidance.
• Improve detection accuracy and minimize false positives.
• Collaborate with cross-functional teams to implement data-driven prevention strategies.
• Stay updated on AI Security trends and mentor teammates.
• Provide data science expertise to Security and Product teams.

Skills

SQL

Python

Anomaly detection

Statistical methods

ML/AI techniques

Data mining

Time series analysis

Spark

Snowflake

Communication

Education

Advanced degree in CS/Statistics/Applied Math

Tools

Claude Code

Cursor AI

Spark

Snowflake

Job description

Zendesk is seeking a Staff Data Scientist to join the AI Security team to envision and develop ML approaches that identify anomalous activity and AI security risks. You will collaborate with Security Engineers, Software Engineers, ML researchers, and product teams to share actionable insights and models for keeping customers safe and preventing product abuse.

Responsibilities include building an evaluation platform, analyzing large-scale data, and mentoring others while staying ahead of AI