Data Scientist

Role overview

Day-to-day responsibilities

• Design, train, and deploy predictive weather and spatio-temporal models using weather feeds and client sales data.
• Analyze meteorological datasets and turn probabilistic trends into strategic recommendations.
• Partner with Sales, Marketing, and Customer Support on B2B analytics solutions.
• Optimize models and inference pipelines using distributed computing and modern machine-learning tools.
• Own model testing, deployment, and monitoring for production reliability.
• Document model architectures, data lineage, and decision logic.
• Work with Data Engineers, Product Managers, and Revenue leaders to embed algorithms in live APIs and deliver scalable data products.

Required qualifications

• Degree in a STEM discipline such as Data Science, Statistics, Computer Science, or another quantitative field.
• At least 3 years of data science experience in B2B environments, including spatio-temporal modeling, time-series forecasting, and weather data intelligence.
• High proficiency in BigQuery and SQL, including window functions, query optimization, and large-scale data manipulation.
• Advanced Python skills and hands-on experience with NumPy, SciPy, Scikit-learn, and TensorFlow or PyTorch.
• Experience with distributed computing frameworks such as Apache Spark for large-scale data processing.
• Strong communication skills, including explaining complex ideas to non-technical audiences.

Preferred qualifications

• A Master's degree or PhD is preferred but not required.
• Experience developing and deploying deep-learning models is a nice-to-have.
• Familiarity with LLM or RAG pipeline deployment is a nice-to-have.

Workplace

• The role uses a hybrid work model at the Oakville location.
• Candidates must be eligible to work in Canada.

Benefits and workplace offerings

• The posting describes a flexible hybrid work environment, retirement savings matching, and spending accounts.
• The posting lists summer hours, 17 paid days off, and 13 personal days.