Senior Data Scientist

Location: b, Canada

Department: Development

Experience: 7+ Years

• Develop and enhance optimization models using MILP and heuristic approaches, applying them to problems such as vehicle routing, scheduling, and resource allocation, and improving performance using solvers such as Gurobi
• Apply machine learning techniques to support decision systems, including predictive modeling, feature engineering, and generating inputs for optimization models, while ensuring strong integration between ML and optimization frameworks
• Translate business requirements into structured analytical and optimization problems, incorporating operational constraints and clearly communicating model assumptions, trade-offs, and outcomes to stakeholders
• Diagnose and resolve model issues including infeasibility, performance bottlenecks, and data inconsistencies, while analyzing trade-offs across cost, service level, and operational feasibility
• Develop and maintain data workflows using Python and SQL, and support scalable processing and deployment within cloud environments such as Azure and Databricks
• Ensure data quality and model reliability by validating inputs, identifying gaps, and supporting feedback loops to improve model accuracy and alignment with operations
• Collaborate with cross-functional teams, take ownership of model components, contribute to technical design discussions, and provide guidance to junior team members

• 8+ years of experience in data science, operations research, or a related field
• Strong hands-on experience in optimization (e.g., MILP, VRP, scheduling) and machine learning
• Proficiency in Python and SQL
• Experience working with optimization solvers such as Gurobi
• Familiarity with Azure and Databricks environments
• Proven ability to translate business problems into data-driven solutions
• Strong problem-solving skills and ability to work in fast-paced environments
• Effective communication skills with both technical and business stakeholders

• Experience in supply chain, logistics, or operations-focused environments
• Familiarity with large-scale optimization techniques or heuristic methods
• Experience working with distributed data systems or cloud-based analytics platforms
• What Success Looks Like
• You will deliver reliable and scalable model components that drive operational decisions, effectively bridge the gap between business and analytics, and contribute to measurable improvements in efficiency, service levels, or cost.