Senior Staff Data Scientist
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Staff Data Scientist based in Canada.
As a Senior Staff Data Scientist, you will join an AI Security team focused on detecting anomalous activity, abuse, and emerging risks across AI-powered products.
You will design and develop machine learning approaches that transform large-scale behavioral data into actionable security insights.
Your work will directly contribute to protecting customers, improving detection accuracy, and reducing false positives.
You will collaborate closely with security engineers, software engineers, ML researchers, and product teams.
The role combines hands-on data science, experimentation, technical leadership, and mentorship.
You will work on challenging problems involving anomaly detection, sparse and unbalanced datasets, and large-scale distributed computing.
This is an opportunity to influence how AI security systems are evaluated, developed, and brought into production.
Accountabilities
Develop and operate AI Security evaluation platforms used to assess AI-powered features and identify potential risks.
Analyze large volumes of behavioral and user interaction data to uncover patterns associated with abuse, anomalies, and security threats.
Automate analytical methodologies and develop scalable approaches for identifying suspicious activity.
Design and implement detection models and techniques using offline data to inform production engineering decisions.
Improve existing spam and abuse detection capabilities while maintaining a strong focus on minimizing false positives.
Partner with security, product, engineering, and research teams to translate data-driven findings into effective prevention strategies.
Monitor developments and emerging trends in AI Security and incorporate relevant techniques into research and detection approaches.
Provide technical leadership across data science initiatives and mentor other team members on complex projects.
Advise cross-functional stakeholders on emerging data challenges, model performance, and appropriate analytical approaches.
Contribute to the development of scalable security solutions that protect customers and reduce product abuse.
Advanced degree in Computer Science, Statistics, Applied Mathematics, or another quantitative discipline, or equivalent practical experience.
At least 5 years of experience applying machine learning or AI to areas such as fraud detection, anomaly detection, cybersecurity, or related problems.
Strong programming skills in Python and SQL, with experience using modern data-processing frameworks.
Demonstrated fluency with AI-assisted programming tools such as Claude Code, Cursor AI, or comparable technologies.
Strong knowledge of statistical modeling, machine learning, data mining, and time-series techniques.
Deep understanding of anomaly detection, including the statistical challenges associated with sparse and highly unbalanced datasets.
Experience working with large-scale datasets and distributed computing environments such as Spark or Snowflake.
Strong analytical and problem-solving abilities, with the capacity to turn complex data into practical security insights.
Excellent communication skills and the ability to explain sophisticated technical concepts to non-technical stakeholders.
Experience implementing anomaly detection or AI Security evaluation systems at scale is highly desirable.
Experience with AI red-teaming tools and knowledge of cybersecurity principles and common attack vectors are strong assets.
Familiarity with ML model monitoring, production maintenance, guardrails, firewall models, and their impact on customers is an advantage.
Ability to provide technical leadership, mentor colleagues, and collaborate effectively across multidisciplinary teams.
Fully flexible work model with the opportunity to work remotely from Canada.
Full-time employment opportunity in a highly technical, collaborative environment.
Opportunity to work on advanced AI Security, machine learning, and anomaly detection challenges at significant scale.
Exposure to multidisciplinary collaboration across security engineering, software engineering, ML research, and product teams.
Opportunities to provide technical leadership and mentor other data science professionals.
Inclusive and diverse workplace culture focused on collaboration, learning, and professional development.
Flexible working environment designed to support both remote work and purposeful in-person collaboration.
Reasonable accommodations available throughout the recruitment and employment process for candidates with disabilities.