We are TRADER, a Canadian leader in digital automotive solutions. Our flagship brands —AutoTrader.ca,AutoSync,Dealertrack Canada and CMS— help Canadians buy, sell, and finance vehicles with confidence. AutoTrader.ca is Canada’s largest automotive marketplace, with over 25 million monthly visits. Through AutoSync, we provide software solutions to 3,500+ dealers, streamlining their operations, marketing, and sales. Dealertrack Canada is the country’s top automotive financing portal, processing more than 6.5 million credit applications each year. Collateral Management (CMS) is a national tech solution that boosts lien and registration services, recovery services, and insolvency management solutions for Canadian lenders. As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond. Join our global Data Science team and contribute to shaping the future of the automotive marketplace through AI and machine learning. As a Data Scientist, you'll work on impactful AI initiatives that influence millions of users worldwide, with a focus on implementation and innovation. In this role, you'll collaborate with product, engineering, and business teams to build and improve AI solutions that set us apart in the industry. You'll apply your technical expertise and analytical mindset to develop ML products that solve real-world problems and deliver business value. Our ideal candidate is a motivated data scientist who thrives in a dynamic, fast-paced environment that combines the stability of an industry leader with the agility of a startup culture. You are curious, proactive, and committed to continuous learning, especially in emerging areas like Generative AI and Large Language Models (LLMs). What You’ll Do Design and implement predictive and generative AI models that power personalization, pricing, search, and optimization in marketplace and fintech domains Work with product and business teams to translate strategic goals into data-driven solutions, owning end-to-end model development for specific product features Extract actionable insights from large, complex datasets, presenting findings clearly to both technical and non-technical audiences Support scalable ML infrastructure using cloud-native tools (e.g., AWS, EC2) to facilitate efficient model training and deployment Take ownership of model performance metrics, conducting regular evaluations and communicating results to stakeholders Lead technical discussions for your areas of ownership during team reviews, advocating for best practices in code quality and model design Participate in code reviews and technical discussions to improve team best practices and model quality Propose creative approaches to solve complex business problems, balancing technical innovation with practical implementation Contribute to exploration of GenAI applications, helping identify use cases and supporting their integration What You’ll Need Advanced academic credentials in a quantitative field such as Computer Science, Engineering, Mathematics, or related discipline 3-5 years of experience in data science, machine learning, or applied AI, with experience deploying models to production Strong programming skills in Python and SQL, and familiarity with ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Experience with machine learning algorithms (supervised, unsupervised, deep learning), including model evaluation and selection Hands‑on experience with cloud infrastructure (AWS), containerization (Docker), and orchestration (Jenkins, Airflow) Understanding of MLOps concepts, including model monitoring and versioning Experience with model deployment through APIs (e.g., Flask, FastAPI) in both real‑time and batch‑processing environments Good communication skills, able to explain technical concepts to different audiences Experience working in agile product development environments (Scrum/Kanban) Experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine‑tuning methods Bonus Points Experience in e-commerce, marketplaces, or high‑scale consumer platforms Familiarity with automotive data and applications in pricing, inventory optimization, or recommendation systems Contributions to open‑source AI/ML projects, publications, or presentations at industry conferences Experience leveraging AI, Generative AI (GenAI) to enhance engineering productivity, automate repetitive tasks, and optimize workflows. Candidates should demonstrate the ability to integrate AI‑driven solutions into their daily work — such as code generation, debugging, reviews, documentation, and decision support—to improve efficiency for themselves and their teams. A proactive approach to exploring and implementing AI tools that drive innovation and streamline development processes is highly valued If this opportunity excites you, but you're unsure whether your background checks every box, we value passion, curiosity, and a growth mindset. Reach out and tell us what strengths you would bring to the team. We look forward to hearing from you! What’s in it for you… We understand that there is life at work and life outside of work. Here are a few benefits we all benefit from that support us to be our creative best. Benefits from Day 1 Employee and Family Assistance program Weekly virtual wellness events Regular internal training programs Annual bonus structure 3% CPP matching For a career where you can drive our business and shape your future, apply now. Use of Artificial Intelligence in Hiring: We use artificial intelligence (“AI”) in our hiring process, including to screen, assess, or select applicants for this position. Vacancy Status: This job posting is for an existing vacancy. Apply for this job * indicates a required field First Name * Last Name * Email * Phone Country * Phone * Location (City) * Resume/CV * Enter manually Accepted file types: pdf, doc, docx, txt, rtf Enter manually Accepted file types: pdf, doc, docx, txt, rtf Please provide your LinkedIn profile * Are you eligible to work in Canada/Germany? * Select... Our Ways of Working require weekly office attendance. Are you open to coming to the office 2 times a week? * Select... 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