Staff Data Scientist - Ads (AI Native)

About the role

The Staff Data Scientist - Ads (AI Native) role is offered by a partner company managing all applications and next steps. This position involves shaping the future of advertising technology through advanced machine learning and AI-native development practices.

Responsibilities

• Design, build, and operate large-scale ML solutions that enhance ad delivery performance and business outcomes.
• Collaborate with cross-functional teams to deploy models into production and optimize critical revenue-generating platforms.
• Transform complex technical challenges into impactful algorithmic systems.
• Define ML best practices and mentor peers to accelerate innovation across the organization.
• Own the development, deployment, and optimization of machine learning systems that power advertising solutions at scale.
• Partner with Product, Data Science, Cloud Engineering, and Data Engineering teams to design, develop, and deploy machine learning and optimization solutions.
• Build, train, deploy, and scale ML models through high-availability services or batch processing workflows.
• Develop algorithms that improve advertising performance, including delivery efficiency, optimization, and system scalability.
• Integrate model outputs directly into production advertising systems.
• Establish monitoring, logging, alerting, and performance tracking frameworks for ML systems, including inference performance, latency, resource utilization, and model drift.
• Create scalable pipelines for experimentation and machine learning workflows with data engineering teams.
• Implement robust data, code, and model lineage practices to support reliability, compliance, reproducibility, and security.
• Leverage AI-native development tools to accelerate implementation, automate workflows, and increase engineering velocity.
• Review and validate AI-generated code, analysis, and models to ensure production quality and technical excellence.
• Mentor other data scientists and contribute to ML architecture decisions, technical standards, and team best practices.
• Participate in production support activities, including handling live system issues and contributing to operational reliability.

Requirements

• Advanced degree in a quantitative field or equivalent professional experience.
• 8+ years of experience designing, implementing, and operating machine learning and optimization systems.
• Strong Python programming skills with expertise in software engineering best practices, including testing, modular design, and version control.
• Experience with ML lifecycle and data processing tools such as MLflow, Kubeflow, SparkML, SQL, Spark/PySpark, dbt, or Airflow.
• Practical experience working within major cloud platforms such as AWS, GCP, or Databricks, including knowledge of cloud infrastructure, networking, security, and storage.
• Experience deploying and operating machine learning models in production environments.
• A strong understanding of data pipelines, experimentation frameworks, and scalable ML architecture.
• Excellent communication skills with the ability to influence cross-functional stakeholders and explain technical concepts clearly.
• Experience leading technical projects and driving initiatives from concept through production.
• A strong problem-solving mindset with the ability to structure complex challenges before selecting solutions.
• A collaborative approach with the ability to balance technical depth, business impact, and team alignment.
• Hands-on experience using AI tools as part of daily development workflows, including delegating implementation tasks, reviewing AI-generated outputs, and improving team productivity.
• Experience solving advertising optimization challenges such as bidding, budget allocation, targeting, or related recommendation systems is a strong asset.

Benefits

• Competitive salary package: Canada-based salary range: $198,000 - $233,000 CAD.
• Equity opportunities as part of the total compensation package.
• Comprehensive medical, dental, vision, life, and disability insurance benefits.
• Retirement savings programs, including RRSP with DPSP plan for Canadian employees.
• Flexible paid time off and company-wide holidays.
• Employee Assistance Program supporting mental wellness.
• Learning and development programs to support career growth.
• Remote-first work environment with equipment, tools, and reimbursement support.
• Opportunity to work on impactful AI and machine learning systems serving millions of users worldwide.
• Inclusive culture focused on collaboration, innovation, and meaningful impact.