Staff Data Scientist - Ads (AI Native)

Accountabilities: The Staff Data Scientist will own the development, deployment, and optimization of machine learning systems that power advertising solutions at scale. This role requires strong technical judgment, hands-on engineering capabilities, and the ability to translate ambiguous business challenges into scalable AI-driven solutions.

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.

Collaborate with engineering teams to 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.

Improve data ecosystems by partnering with data engineering teams to create scalable pipelines for experimentation and machine learning workflows.

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:

The ideal candidate is an experienced data science professional with deep expertise in machine learning engineering, production ML systems, and AI-driven development. They should combine strong technical skills with excellent communication abilities and a passion for solving complex problems collaboratively.

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.

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.

Strong problem-solving mindset with the ability to structure complex challenges before selecting solutions.

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.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether? 

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