Senior Data Scientist

WestJet Group•Calgary, AB

5d•Onsite

About The Position

This position requires in-person collaboration up to five days a week. This arrangement is subject to change based on business requirements. Why WestJet: Since our story took off in 1996, WestJet has strived to enrich the lives of everyone in our world; a career with us is no exception. We’re proud to be one of Canada’s most admired and respected corporate cultures and continuously aim for the highest standards of service and success. Join us, this is where your career story takes off. We are seeking a talented and experienced Senior Data Scientist to join the Data Science & Strategic Insights team. If you are passionate about data, have a proven track record of solving complex problems, and want to contribute to meaningful projects, we encourage you to apply. As a Senior Data Scientist at WestJet, you will play a crucial role in driving data-driven decision-making and delivering actionable insights. You will work collaboratively with cross-functional teams, including data engineers, product managers, and business stakeholders, to design, develop, and deploy advanced analytics and AI solutions.

Requirements

Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative discipline, combined with 6+ years of progressive experience in data science, machine learning, artificial intelligence, or advanced analytics.
Advanced proficiency in Python and SQL, with hands-on experience using modern data science, machine learning, and AI libraries, frameworks, and development environments.
Strong foundation in statistics, machine learning, and data science methodologies, including supervised and unsupervised learning, predictive modeling, experimentation, optimization, and statistical analysis.
Demonstrated experience designing, developing, validating, and deploying statistical and AI/ML models within enterprise production environments.
Hands-on experience developing Generative AI and Agentic AI solutions, including large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), embeddings, vector databases, semantic search, tool integration, and orchestration frameworks.
Experience working within modern AI/ML development environments, including Git-based version control, CI/CD processes, MLOps frameworks, model lifecycle management, and collaborative software development practices that enable scalable and repeatable delivery of AI/ML solutions.
Experience with model lifecycle management, including model monitoring, performance evaluation, data and concept drift detection, versioning, and retraining strategies to maintain long-term model accuracy and reliability.
Experience translating analytical findings into actionable business insights through data visualization and storytelling, including the development of executive-ready decks and dashboards using tools such as Power BI or Streamlit.
Experience working within modern cloud-based data platforms, preferably Snowflake.
Excellent analytical, problem-solving, communication, and stakeholder management skills, with a demonstrated ability to influence decisions, navigate ambiguity, and communicate complex analytical concepts to both technical and non-technical audiences.

Nice To Haves

A Master’s and/or Ph.D. in Data Science, Statistics, Computer Science, or a related field.
Formal generative and agentic AI training or certification.
Prior experience working for an airline

Responsibilities

Identify opportunities to apply machine learning, generative and agentic AI, and advanced analytics techniques to business challenges, ensuring solutions are aligned with organizational priorities and expected business outcomes.
Conduct exploratory data analysis across structured and unstructured data sources to identify patterns, trends, risks, and opportunities that inform model development and AI solution design.
Prepare, transform, and engineer features from multiple structured and unstructured data sources to support model development, experimentation, and AI applications.
Develop, train, and optimize statistical, machine learning, and AI models that improve decision-making by generating actionable insights and recommendations.
Design and prototype AI solutions using large language models, prompt and context engineering, embeddings, semantic search, retrieval-augmented generation, and agentic workflows to augment employee productivity and business capabilities.
Evaluate model performance using appropriate statistical techniques and ensure outputs are explainable, interpretable, and actionable for business stakeholders.
Communicate analytical findings and insights through effective storytelling, clear business narratives, compelling visualizations and executive-level presentations executive-ready insights in collaboration with the technical product owner.
Collaborate closely with product owners, engineers, platform teams, visualization specialists and architects to ensure analytical solutions are technically feasible, scalable, interpretable, and aligned with business objectives.
Serve as a subject matter expert in data science and AI by mentoring team members, sharing knowledge, evaluating emerging technologies, and advancing analytical best practices across the organization.