Data Scientist

About this role Our mission is to enable smarter business decisions and create intelligent apps and workflows so customers see the most relevant content at the right time. As a founding member of this team, you will be instrumental in architecting the systems and delivering the first data science models into production across personalization and other business-critical areas from the ground up.You will lead end-to-end data science projects, translating business problems into production-ready solutions.Lead projects from concept to deployment, collaborating with Engineering to ensure models are scalable, performant, and fully integrated.Apply Causal Inference to model the impact of internal and external events on order volume and business forecasting.Drive technical excellence through active peer reviews, prioritizing both mentorship and continuous personal coaching.Leverage cutting-edge AI tools to accelerate development and build innovative, high-scale solutions.Solve complex problems using a first-principles approach, emphasizing knowledge sharing and a culture of continuous learning.Location: Hybrid- 3 days a week from our Toronto office & 2 days working from homeReporting to: Senior Manager- Data Science These are some of the key ingredients to the role: Full-Stack Ownership: Operate as a versatile data scientist in a fast-paced startup environment, maintaining high standards and a customer-obsessed approach to problem-solving.Cross-Functional Collaboration: Bridge the gap between technical and business teams; translate complex model tuning and technical trade-offs into actionable insights for Product Managers and stakeholders.End-to-End Delivery: Lead complex algorithmic initiatives from initial concept to production, ensuring the rigor and performance required for real-world application.Engineering Excellence: Champion the "model-as-part-of-a-system" philosophy, taking ownership of the underlying data pipelines and navigating cloud infrastructure to self-serve resource needs.Pragmatic Problem Solving: Balance theoretical depth with practical constraints, selecting the right tool for the job—whether deep learning or robust signal processing—based on the specific use case.Simplified Innovation: Solve complex problems by valuing simplicity in system design, ensuring that solutions remain scalable and maintainable.Continuous Growth: Maintain a growth mindset, proactively seeking out new methodologies and better ideas to improve existing systems.What will you bring to the table? Production ML Expertise: 3–5+ years of experience building and deploying live models, moving projects seamlessly from notebook to production.Technical Stack: Proficient in Python and SQL, with hands-on experience in BigQuery, Vertex AI, and DynamoDB.Cloud & DevOps Autonomy: Comfortable managing cloud infrastructure (AWS/IAM) and orchestration tools like Airflow to build and unblock your own pipelines.Strategic Communication: Ability to translate complex technical trade-offs for Product Managers and stakeholders while maintaining a "customer-first" mindset.Pragmatic Innovation: A versatile problem solver who knows when to use deep learning vs. simpler methods and is familiar with Vector Embeddings or Forecasting.At JET, this is on the menu: Our teams forge connections internally and work with some of the best-known brands on the planet, giving us truly international impact in a dynamic environment. Fun, fast-paced and supportive, the JET culture is about movement, growth and about celebrating every aspect of our JETers. Thanks to them we stay one step ahead of the competition.