Being part of Air Canada is to become part of an iconic Canadian symbol, recently ranked the best Airline in North America. Let your career take flight by joining our diverse and vibrant team at the leading edge of passenger aviation.
As a Data Scientist - Operations Research and Optimization at Air Canada, you will drive the analytical scope and methodology for projects using Optimization, Data Science, Simulation, Mathematics, Statistics, and Business Acumen to derive structure and knowledge from raw data and business rules. We are looking for an Operations Research Scientist to help us formulate business problem, objective, and constraints into solvable model and help us make smarter decisions to deliver even better products and services. Your primary focus will be in applying Operation Research techniques integrated with our products and services.
In this role, you will join the AI-CoE (Center of Excellence), a central group within Air Canada’s IT organization that builds Machine Learning and Optimization solutions to internal business units including Revenue Management, Network Planning, Operations, Maintenance, and Cargo organizations. The team primarily comprises of Data Scientists, Data Engineers, Operations Research Scientists, Machine Learning Engineers, and Delivery Leads. As you join a project to deliver a deployable production-grade application to one of our business stakeholders, you will collaborate with Business Sponsors, Product Owners, Business Analysts and SEM(s), DevOps, Solution Architects, UX Designers, Full-stack Developers, and QA engineers. All projects are executed in agile mode, following 2-3 weeks sprints, with incremental releases leading to the final production release.
- Use optimization techniques to formulate, solve business problems, and build in-house decision-support systems.
- Apply decomposition methods as needed to solve very large-scale models.
- Develop and implement scalable quantitative mathematical models and collaborate with engineers to deploy these models.
- Perform quantitative, economic, and numerical analysis of the performance of these systems to find both exact and heuristic solution strategies for optimization problems.
- Apply mathematical optimization techniques, including Linear Programming, Integer Programming, Dynamic Programming, Network Optimization algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software.
- Apply Machine Learning and regression techniques to tackle predictive modeling problems.
- Create software prototypes to verify and validate the devised solutions methodologies.
- Investigate the conflict behind infeasible datasets and add appropriate handling to resolve such infeasibilities.
- Establish processes for large-scale data analyses, model development, model validation and model implementation.
- Develops complex models and algorithms that drive innovation throughout the organization.
- Can objectively weigh trade-offs of different algorithms and models.
- Guide data engineering efforts to ensure alignment with future optimization engine needs.
- Performing quality assessments of analytical solutions, particularly simulation and optimization models.
- Lead requirement and systems analysis efforts, including translating business requirements into quantitative mathematical models.
- Establish and maintain effective business relationships.
- A Master’s Degree or PhD in Operations Research, Computer Science, Engineering, Applied Mathematics, Statistics, or Quantitative Methods and/or relevant experience commensurate to the role.
- 3 - 5 years of related work experience.
- Proficiency in using one of the commercial solvers like Cplex, Gurobi, or Fico Xpress, or non-commercial solvers like Coin-OR or SCIP.
- Strong background in optimization techniques to solve Mixed Integer Programming (MIP), Quadratic Programming (QP), or Non-Linear Programming (NLP).
- Fluency in at least one programming or scripting language (e.g. Python, Java, C, C++, C#).
- Experience in SQL and querying large datasets.
- Experience in applying Operations Research, advanced analytical and/or statistical methods to solve business problems.
- Experience with fast prototyping.
- Familiarity with Network Optimization, Large Scale Neighborhood Search.
- Familiarity with Machine Learning models and algorithms.
- Excellent presentation and verbal/written communication skills, with the ability to explain complex analytical concepts to people from other fields.
- Self-motivated and highly independent.
- Strong problem solving and data analysis skills.
Conditions of Employment:
Based on equal qualifications, preference will be given to bilingual candidates.
Diversity and Inclusion
Air Canada is strongly committed to Diversity and Inclusion and aims to create a healthy, accessible and rewarding work environment which highlights employees’ unique contributions to our company’s success.
As an equal opportunity employer, we welcome applications from all to help us build a diverse workforce which reflects the diversity of our customers, and communities, in which we live and serve.
Air Canada thanks all candidates for their interest; however only those selected to continue in the process will be contacted.