And for more than 90 years, our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.
Allstate Insurance Company of Canada is a leading home and auto insurer focused on providing its customers prevention and protection products and services for every stage of life. Serving Canadians since 1953, Allstate strives to reassure both customers and employees with its “You’re in Good Hands®” promise and is proud to have been named a Best Employer in Canada for nine consecutive years. Allstate is committed to making a positive difference in the communities in which itoperatesthrough partnerships with charitable organizations, employeegivingand volunteerism. Through our Employee Value Proposition, we have worked hard to develop and nurture a culture where employees feel valued, experience personal growth, have careeroptionsandtruly enjoythe work they do.
Flexible Work Arrangements.
Employee discounts (15% on auto and property insurance, plus many other products and services).
Good Office program (receive up to $400 back afterpurchasingoffice equipment).
Comprehensive Retirement Savings Program withemployer matchedcontributions.
Personal days.
Working within the community and giving back.
In this role,you’llhave a front-row seat to the entire insurance ecosystem—claims, underwriting, pricing, and even broader business areas like HR and marketing. you’llwork on high-impact projects that drivereal results. From day one,you’lldive into stakeholder data,



blending quantitative insights with businessexpertiseto build predictive models that shape smarter decisions. You’llcollaborate closely with fellow data scientists and business leaders, turning ideas into strategies that improve performance and strengthen the bottom line.
Lead the end-to-end development, deployment, and monitoring of predictive models supporting Lifetime Value (LTV), Loss Cost, pricing, retention, and profitability initiatives within the insurance business.
Translate complex business problems into scalable analytical solutions by partnering closely with stakeholders across Product, Pricing, Marketing, Claims, and Finance.
Develop, validate, and maintain advanced machine learning, statistical, and predictive models, ensuring strong model performance, interpretability, and business value.
Deploy and operationalize models using Azure Machine Learning, Microsoft Fabric, and modern MLOps practices, ensuring reliability, scalability, and governance compliance.
Communicate analytical findings, model insights, and recommendations to technical and non-technical audiences, enabling data-driven decision making.
Provide thought leadership on customer value, risk, profitability, and growth opportunities through advanced analytics and data science innovation.
Demonstrated experience in machine learning and analytics, ideally within a professional services firm or similar environment,



with a strong background in implementing and optimizing machine learning algorithms to solve regression, classification, and segmentation problems
Proven experience developing and deploying machine learning and statistical models in a business environment, ideally within Property & Casualty (P&C;) insurance, financial services, or other data-intensive industries.
Advanced programming skills in Python and SQL, with hands-on experience using up-to-date machine learning libraries and data science frameworks.
Experience working with Azure Machine Learning, Microsoft Fabric, cloud-based analytics platforms, and production model deployment workflows.
Strong understanding of data preparation, feature engineering, model validation, experimentation, and performance monitoring best practices.
Excellent communication and stakeholder management skills, with the ability to explain complex analytical concepts to business audiences and senior leaders.
Bonus Qualifications

Working knowledge of SAS and experience supporting or modernizing legacy analytical environments is considered an asset.
Experience with MLOps, model governance, responsible AI practices, and production-scale machine learning solutions is considered a strong asset.
Allstate Canada Group has policies and practices that provide workplace accommodations. Analytics, Azure Machine Learning, Data Science, Machine Learning Algorithms, Machine Learning Model Development, Model Deployment, Python (Programming Language), Statistical Models, Structured Query Language (SQL)
Allstate Canada Group uses AI technology tools to assist in screening, selecting, assessing, and scheduling interviews with candidates as part of the recruitment process.

📌 Data Scientist - Data Science - F/H (Toronto)
🏢 Allstate
📍 Toronto