Manager, Data Science at Four Seasons… · Toronto

Manager, Data Science Location: Four Seasons Corporate Office Toronto About Four Seasons: Four Seasons is powered by our people. We are a collective of individuals who crave to become better, to push ourselves to new heights and to treat each other as we wish to be treated in return. Our team members around the world create amazing experiences for our guests, residents, and partners through a commitment to luxury with genuine heart. We know that the best way to enable our people to deliver these exceptional guest experiences is through a world-class employee experience and company culture. At Four Seasons, we believe in recognizing a familiar face, welcoming a new one and treating everyone we meet the way we would want to be treated ourselves. Whether you work with us, stay with us, live with us or discover with us, we believe our purpose is to create impressions that will stay with you for a lifetime. It comes from our belief that life is richer when we truly connect to the people and the world around us. About the location: Four Seasons Hotels and Resorts is a global, luxury hotel management company. We manage over 130 hotels and resorts and 50 private residences in 47 countries around the world and growing. Central to Four Seasons employee experience and social impact programming is the company’s commitment to supporting cancer research, and the advancement of diversity, inclusion, equality and belonging at Four Seasons corporate offices and properties worldwide. At Four Seasons, we are powered by people and our culture enables everything we do. Manager, Data Science (12 Month Contract) The Manager, Data Science is an applied data science leader within the Data & Analytics function and part of the Technology Innovation & Data (TID) department, supporting Commercial and enterprise-wide initiatives. This role bridges business challenges and technical execution—owning problem framing, analytical approach, modeling/experimentation/measurement, and stakeholder alignment to deliver clear business outcomes (e.g., revenue growth, cost savings, improved guest experience). Reporting to the Director, Data Science & Analytics, this role will work cross-functionally with Data Engineering, Data Governance, and Data Delivery, the Manager, Data Science will apply Four Seasons’ technical standards to operationalize AI solutions from prototype to production. What You’ll Be Doing: Lead Data Science in Designing Prototypes Supporting Commercial Strategy Own applied data science problem framing: translate business goals into clear hypotheses, success metrics, and an analytical approach (e.g., forecasting, propensity, segmentation, optimization, NLP). Lead the design and delivery of data science prototypes aligned to commercial strategy, ensuring measurable business impact (e.g., cost savings, revenue growth, improved guest experience). Define and execute measurement and experimentation plans (e.g., A/B tests, holdouts, quasi-experiments) to quantify incremental impact and guide product/business decisions. Plan and manage the data science / ML project pipeline by developing roadmaps, aligning business priorities, communicating tradeoffs, and coordinating dependencies with partners (e.g., Data Engineering, Data Governance, Product/Digital/Business teams). Identify, collect, and validate datasets; define data quality checks and partner with data stewards/engineering to ensure data is fit for purpose. Design, develop, and evaluate models and prototypes; select the best approach balancing accuracy, interpretability, scalability, and business constraints. Present insights and recommendations to non-technical and leadership audiences, driving alignment, decision-making, and adoption. Raise the bar on team quality: conduct peer code reviews, mentor team members, and document approaches (Confluence) to establish reusable patterns and best practices. As applicable, manage third parties during the prototyping phase to ensure schedules, processes, and outcomes are monitored and achieved. Support Machine Learning Deployments Develop, test, optimize, and productionize machine learning models, including their supporting data pipelines for training and predictions. Develop and embed automated processes for predictive model validation and QA. Stage deployments to enable collaborative QA and controlled releases, monitor and version control changes. Monitor health and performance of production ML products and relative performance of competing models. Promote, contribute, and define coding guidelines to raise the bar for code quality. Develop and Support Generative AI Solutions Develop and optimize Gen AI workflows using LLMs, RAG, vector search, and AI orchestration frameworks. Partner with engineering, integrations, and platform teams to support deployment of LLM-based applications, including retrieval pipelines, and prompt orchestration and governance across development and production environments. Design evaluation suites and QA approaches for GenAI solutions (e.g., test sets, automated checks, human review), including responsible AI guardrails appropriate to the use case. Contribute to reusable AI components, prompt engineering standards, and AI solution design best practices. Partnerships and Following Four Seasons Standards Follows technical direction set by Enterprise Data Architect and Data Engineering team. Manage data science projects from conception to delivery through the organized intake process, track tasks and progress using Jira and Monday.com, and adhere to governance standards and successful delivery methodologies. Learn and implement Four Seasons technical standards, procedures and processes including FS DevOps. Test and verify the completion of work done by Data Engineering to ensure compliance with the original intent of prototype and long-term requirements. What You Bring: 5+ years of working experience in data science, data wrangling, management, and/or ML engineering. University degree in Computer Science, Statistics, Data Science, Applied Mathematics, Engineering, or substantial coursework in relevant quantitative field. Applied modeling and analytics: strong foundation in statistics and ML (supervised/unsupervised), feature engineering, and model evaluation; ability to explain tradeoffs and drive business decisions. Experience in NLP and/or GenAI techniques for applied use cases (e.g., classification, entity extraction, semantic search) with an evaluation-first mindset. Data proficiency: advanced SQL and Python; strong data wrangling skills (profiling, cleansing, merging, validation) for large, messy datasets. Cloud & tooling (preferred): Azure and Databricks ecosystem (e.g., Databricks, Data Factory, Data Lake/Blob, Azure Function App, Azure AI Foundry), with ability to run scalable experimentation and modeling workflows. Production readiness (in partnership with Engineering): familiarity with CI/CD, version control (Azure DevOps/GitHub), reproducible pipelines, and monitoring principles for models and data products. Visualization & communication: experience using notebooks and BI tools (e.g., Power BI, Tableau, PowerPoint) to tell clear stories to technical and non-technical stakeholders. Experimentation and measurement: experience designing and interpreting experiments (A/B tests, holdouts, quasi-experiments) and defining success metrics for product/business outcomes. Who You Are: Proactive to understand business needs and how data will be used to drive strategic decisions and tactical action plans. Translates data science outputs to provide clear, actionable recommendations that support leadership decision-making. Tailors messaging to the audience, focusing on clarity, brevity, and relevance. Collaborate effectively with cross-functional colleagues, external consultants, and agencies. Works well under pressure and can manage multiple tasks under time constraints. Well organized, detail-oriented, able to multi-task in a highly iterative environment. Creative, performance-driven problem solver with a strong sense of ownership and discipline; passionate about leveraging digital, AI, ML, and data to drive business transformation. Solid foundation in Math and Statistics. Ability to sift through large data sets, identify patterns and know how to use that data to come to meaningful and actionable conclusions. Work cross-functionally in a matrix organization. Project Management: Organize and manage processes and expectations, and deliver according to key deadlines. Salary Range: $85,000 - $125,000 This role will be a Hybrid working model, which will require 3 days per week at our temporary 20 York Mills Road, Toronto, Ontario location with travel, as needed, to our the Four Seasons Corporate Office located at 1165 Leslie Street, Toronto, Ontario #LI-Hybrid Four Seasons is committed to providing employment accommodation in accordance with the Ontario Human Rights Code and the Accessibility for Ontarians with Disabilities Act. If contacted for an employment opportunity, please advise Human Resources if you require accommodation.