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AutoTrader.ca

AutoTrader.ca

go.trader.ca

4 Jobs

1,040 Employees

About the Company

AutoTrader.ca is the leading advertising partner for Canadian automotive retailers and manufacturers. With over 25.7 million visits a month and more than 6 million total mobile app downloads, our largest automotive marketplaces - AutoTrader.ca and AutoHebdo.net - are the #1 source for all things automotive in Canada. The company offers retailers and manufacturers access to a robust audience of new and used car shoppers, best-in-class advertising services and rich data insights. AutoTrader.ca is proud to be the first to offer a completely integrated digital retail experience for consumers and dealers on a major Canadian automotive marketplace.

Listed Jobs

Company background Company brand
Company Name
AutoTrader.ca
Job Title
Software Engineer
Job Description
**Job Title** Software Engineer – Full Stack Cloud **Role Summary** Design, develop, and maintain scalable full‑stack cloud solutions for a high‑traffic automotive retail platform. Provide technical leadership to junior engineers, establish documentation standards, and collaborate with cross‑functional teams to ensure reliability, performance, and security of applications in cloud environments. **Expectations** - Deliver production‑ready, maintainable code in C# and React. - Mentor and code‑review peers, advocating best practices in architecture, testing, and DevOps. - Communicate technical concepts clearly to technical and non‑technical stakeholders. - Lead root‑cause analysis, production support collaboration, and performance optimization initiatives. **Key Responsibilities** 1. Analyze business requirements, design architecture, and implement full‑stack features. 2. Write automated unit, component, and integration tests; enforce test coverage. 3. Develop, maintain, and improve CI/CD pipelines using GitHub, Azure DevOps, and JIRA. 4. Mentor junior developers on design patterns, code reviews, and scalable practices. 5. Create and enforce engineering documentation standards across teams. 6. Conduct root‑cause analysis and coordinate with production support to resolve incidents. 7. Evaluate third‑party solutions and participate in technology selection. 8. Manage deployments across Azure and AWS, including migration activities. 9. Participate in agile ceremonies (Scrum/Kanban, Gitflow) and continuous improvement. **Required Skills** - Strong proficiency in C# (backend) and React (frontend). - Experience with Azure and AWS (including migration). - Knowledge of Kafka, SQL, event‑driven and microservices architecture. - Familiarity with performance tuning, security, and high‑traffic web applications. - Experience with DataDog, Azure Application Insights, and responsive front‑end design. - Expertise in automated testing (unit, component, integration). - Proficiency with Git, GitHub, Azure DevOps, and JIRA in distributed teams. - Solid understanding of Agile methodologies (Scrum, Kanban, Gitflow). - Excellent written and verbal communication skills. **Preferred Skills** - Experience with Java or Scala. - Hands‑on knowledge of Kafka, DataDog, and Application Insights. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Software Engineering, or related technical field (or equivalent practical experience). - No specific certifications required, though cloud and DevOps certificates (e.g., Azure/AWS, Scrum Master) are a plus.
Toronto, Canada
On site
20-12-2025
Company background Company brand
Company Name
AutoTrader.ca
Job Title
Principle Data Scientist
Job Description
**Job Title:** Principal Data Scientist **Role Summary:** Lead the organization’s AI/ML strategy for automotive marketplace products. Design, deploy, and govern predictive & generative models that drive personalization, pricing, search, and fintech services. Provide technical mentorship, shape cross‑functional architecture, and champion innovation in Generative AI. **Expectations:** - Deliver measurable business outcomes with AI solutions. - Mentor and grow a high‑performance data science team. - Align ML initiatives with product and company goals. - Ensure model reliability, compliance, and governance. - Stay current on GenAI/LLM advancements and drive adoption. **Key Responsibilities:** 1. Define strategic vision for data science and identify transformative AI opportunities. 2. Own end‑to‑end design, training, deployment, and monitoring of predictive & generative models (personalization, pricing, search, optimization). 3. Collaborate with product leaders to embed ML into roadmaps and experimentative product cycles. 4. Architect scalable ML infrastructure using cloud‑native tools (AWS, EC2, Kubernetes, Docker, Airflow). 5. Implement robust MLOps pipelines: CI/CD, versioning, automated retraining, model monitoring, and governance. 6. Serve as technical advisor for complex modeling challenges and act as escalation point for critical incidents. 7. Mentor junior data scientists, fostering continuous learning and innovation. 8. Partner with engineering, product, and platform teams to influence architecture, standards, and cross‑functional initiatives. 9. Explore and prototype GenAI/LLM use‑cases, oversee fine‑tuning, deployment, and integration. 10. Translate technical insights into executive‑level recommendations. **Required Skills:** - Advanced programming in Python and SQL; proficiency in scikit‑learn, TensorFlow, PyTorch. - Deep experience with GenAI/LLM tools: Hugging Face, LangChain, OpenAI APIs, vector databases, and fine‑tuning techniques. - Mastery of ML algorithms (supervised, unsupervised, deep learning), evaluation, explainability, and business‑critical selection. - Hands‑on cloud engineering (AWS), containerization (Docker), orchestration (Kubernetes, Jenkins, Airflow). - Proven MLOps expertise: CI/CD, model monitoring, version control, automated retraining. - API deployment skills (Flask, FastAPI) for real‑time and batch services. - Strong stakeholder communication, the ability to distill complex concepts for all audiences. - Leadership and mentorship ability; experience leading data science teams. **Required Education & Certifications:** - Ph.D. or Master’s in Computer Science, Engineering, Mathematics, or related quantitative field (advanced academic credentials). - 10+ years of data science / machine learning experience with a portfolio of production‑grade projects. - Relevant certifications in cloud (AWS Certified Solutions Architect/ML), data engineering, or ML (optional but preferred).
Toronto, Canada
On site
Senior
23-12-2025
Company background Company brand
Company Name
AutoTrader.ca
Job Title
Data Scientist
Job Description
Job Title: Data Scientist Role Summary: Data Scientist responsible for designing, implementing, and deploying AI and machine learning solutions that power personalization, pricing, search, and optimization across automotive marketplace and fintech domains. Collaborates with product, engineering, and business teams to translate strategic objectives into data‑driven products, ensuring end‑to‑end model development, evaluation, and operational excellence. Expectations: - Deliver production‑ready predictive and generative models that influence millions of users. - Own full model lifecycle: data extraction, feature engineering, training, evaluation, deployment, monitoring, and refinement. - Communicate insights and performance metrics to stakeholders in a clear, actionable manner. - Maintain high code quality, adhere to best practices in MLOps, and contribute to continuous improvement of team practices. Key Responsibilities: 1. Design and implement supervised, unsupervised, deep learning, and generative AI models for personalization, pricing, search, and optimization. 2. Translate product and business goals into data‑driven solutions, owning end‑to‑end model development for specific product features. 3. Extract actionable insights from large, complex datasets and present findings to technical and non‑technical audiences. 4. Build scalable ML infrastructure using cloud‑native tools (e.g., AWS, EC2), containerization (Docker), and orchestration (Jenkins, Airflow). 5. Deploy models via APIs (Flask, FastAPI) for real‑time and batch processing, ensuring monitoring, versioning, and MLOps compliance. 6. Lead technical discussions, code reviews, and best‑practice advocacy within the team. 7. Explore and integrate Generative AI and LLM applications, identifying use cases and facilitating implementation. 8. Propose innovative solutions to complex business problems while balancing feasibility and business impact. Required Skills: - Advanced proficiency in Python and SQL; familiarity with ML/AI frameworks such as scikit‑learn, TensorFlow, PyTorch. - Deep knowledge of machine learning algorithms, model evaluation, selection, and tuning. - Hands‑on experience with AWS, Docker, Jenkins, Airflow, and related cloud and CI/CD tools. - Understanding of MLOps concepts, model monitoring, versioning, and deployment via RESTful APIs. - Strong communication skills to explain technical concepts across audiences. - Experience in agile product development (Scrum/Kanban). - Proficiency with GenAI/LLM technologies: Hugging Face, LangChain, OpenAI APIs, vector databases, fine‑tuning. Required Education & Certifications: - Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related quantitative discipline. - 3–5 years of professional experience in data science, machine learning, or applied AI with a proven track record of deploying models to production. ---
Toronto, Canada
On site
Junior
09-01-2026
Company background Company brand
Company Name
AutoTrader.ca
Job Title
Data Analyst - Central Analytics
Job Description
**Job title:** Data Analyst – Central Analytics **Role Summary:** Own the operational KPI reporting for AutoTrader Canada Marketplace, establishing governance, defining core KPI standards, translating business needs into technical specifications, and delivering data products (datasets, pipelines, semantic layers, dashboards). Serve as the central marketing analytics SME, collaborating with stakeholders and data teams to ensure accurate measurement, attribution, and experiment design across the organization. **Expactations:** - Deliver end‑to‑end KPI reporting that is reliable, auditable, and aligns with legal, ops, and business standards. - Act as the single accountability point for core KPI definitions, sources, and published truth. - Translate business requirements into technical specifications for data modeling and reporting. - Present insights, stories, and recommendations to senior leadership and technical teams. **Key Responsibilities:** - Establish and enforce best practices for core KPI governance, change management, lineage, and observability. - Own creation and maintenance of datasets, ETL/ELT pipelines, semantic models, dashboards, and automated reports. - Interface with business stakeholders, data engineers, tracking experts, and platform teams to ensure correct instrumentation, UTM standards, and campaign structures. - Serve as subject‑matter expert in marketing analytics, advising on campaign measurement, attribution, experiment design, and KPI selection. - Collaborate with the AS24 Marketing Analytics team on shared measurement frameworks, best practices, and joint cross‑company analyses. - Conduct deep‑dive analyses, driver work, and performance diagnostics to identify levers and recommend actions. - Produce executive‑grade storytelling and presentations tailored to both business and technical audiences. - Define and maintain documentation, playbooks, and runbooks for KPI consistency and analytics self‑service. **Required Skills:** - SQL and analytic engineering tools (dbt, orchestration). - Cloud data warehouse experience (BigQuery, Redshift, Snowflake). - Semantic modeling and BI dashboarding (Amazon QuickSight, Tableau, or similar). - Marketing analytics expertise: campaign measurement, attribution, lifecycle metrics, experiment design, incrementality testing. - Instrumentation governance, UTM conventions, and collaboration with tracking specialists/MMPs. - Strong stakeholder management, influencing, and presentation skills for senior/executive audiences. - Fluency in English. **Required Education & Certifications:** - Bachelor’s degree in marketing analytics, economics, data science, statistics, or a related field. - Several years of experience in marketing analytics, growth analytics, digital marketing measurement, or data‑driven consulting, preferably in a marketplace or B2C environment.
Toronto, Canada
On site
19-01-2026