Ads AI Analyst at Jobgether – Canada Creek, Nova Scotia

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Ads AI Analyst in Canada.

This role sits at the intersection of advertising analytics, machine learning, and AI-driven product development, focused on building intelligent systems that optimize advertising performance at scale. You will design and operationalize the semantic and data foundations that power next-generation Ads AI agents, enabling automated insights, recommendations, and decision-making across campaigns. The position plays a critical role in improving revenue efficiency and advertiser outcomes by leveraging advanced analytics, experimentation, and retrieval-based AI systems. You will work in a highly cross-functional environment, partnering with product, data science, and engineering teams to translate complex advertising challenges into scalable AI solutions. This is a highly technical and impactful role where your work directly influences ROAS, pacing accuracy, and commercial performance. You will help shape the future of automated advertising intelligence in a fast-moving, data-first organization.

• Define and maintain Ads data ontologies, including campaigns, budgets, creatives, audiences, bids, and placements.
• Build and optimize dbt models and curated datasets in Snowflake or equivalent warehouse environments.
• Design and manage data pipelines, ensuring high-quality, tested, and well-documented data contracts.
• Develop and improve retrieval-augmented generation (RAG) workflows for Ads intelligence systems.
• Ingest, structure, and enrich unstructured advertising data into retrieval-ready datasets for AI agents.
• Define evaluation frameworks for Ads AI systems, including precision, recall, latency, and hallucination metrics.
• Design and run A/B tests and uplift experiments to measure impact and improve model and agent performance.
• Translate advertising business problems into AI agent behaviors and measurable KPIs (ROAS, CTR, CVR, pacing, etc.).
• Collaborate closely with engineering, product, and data science teams to deploy production-ready AI systems.
• Monitor and optimize performance of Ads intelligence systems to ensure reliability, accuracy, and scalability.

Requirements:

• 3–6+ years of experience in analytics engineering, data science, applied AI, or data product roles.
• 2+ years of experience working with advertising, e-commerce, or retail data domains.
• Strong proficiency in SQL and Python for data modeling, analysis, and automation.
• Hands-on experience with dbt and Snowflake or BigQuery, including data modeling and testing.
• Experience building and orchestrating data pipelines using tools such as dbt and Airflow.
• Strong understanding of advertising metrics such as ROAS, CTR, CPA, CVR, LTV, and incrementality.
• Experience designing A/B tests, uplift experiments, and evaluation frameworks for data or AI systems.
• Familiarity with BI tools such as Tableau, Looker, Power BI, or Mode.
• Strong understanding of ML concepts including forecasting, anomaly detection, and recommendation systems.
• Excellent communication skills with a proven ability to deliver production-grade data or AI products.
• Nice to have: experience with RAG systems, evaluation guardrails, and human-in-the-loop workflows.
• Nice to have: exposure to retail media platforms such as Amazon Ads, Google Ads, Meta Ads, or similar ecosystems.

Benefits:

• Competitive annual compensation aligned with the Canadian market (~115,000–121,500 CAD base salary)
• Equity grant and annual refresh equity opportunities
• Fully remote work with Flex First culture across eligible Canadian provinces
• Comprehensive health, dental, and vision coverage
• Paid time off and flexible vacation policy
• Access to learning and professional development resources
• Inclusive, collaborative, and innovation-driven work culture
• Opportunity to work on large-scale AI-powered advertising systems
• Exposure to cutting-edge applied AI and experimentation frameworks
• Strong cross-functional collaboration in a high-impact product environment