At Allstate, great things happen when our people work together to protect families and their belongings from life's uncertainties. 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.

Who is Allstate

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 it operates through partnerships with charitable organizations, employee giving and volunteerism. To learn more, visit For safety tips and advice, visit

Role Designation

Hybrid

Benefits To Joining Allstate

- 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 after purchasing office equipment).
- Student Loan Payment Matching Program for Government Student loans.
- Comprehensive Retirement Savings Program with employer matched contributions.
- Annual Wellness allowance to support employees with improving health and wellbeing.
- Personal days.
- Tuition Reimbursement.
- Working within the community and giving back.

Job Description

In this role,



you'll have a front-row seat to the entire insurance ecosystem - claims, underwriting, pricing, and even broader business areas like HR and marketing. You won't just observe; you'll work on high-impact projects that drive real results. From day one, you'll dive into stakeholder data, blending quantitative insights with business expertise to build predictive models that shape smarter decisions. Your work will go beyond theory - every model you create will deliver actionable insights and innovative solutions that move the needle for the company. You'll collaborate closely with fellow data scientists and business leaders, turning ideas into strategies that improve performance and strengthen the bottom line.

Accountabilities

- 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 robust model performance, interpretability, and business value.
- Deploy and operationalize models using Azure Machine Learning 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.

Qualifications

- 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 modern machine learning libraries and data science frameworks.
- Experience working with Azure Machine Learning or other 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

📌 Data Scientist (Toronto)
🏢 Allstate Canada
📍 Toronto