Allstate

Data Scientist

Canadian Head Office

Live, first seen by us 54 days ago

Pay: $80,900–129,725/year — pay source
Compensation Expected compensation for this role ranges from $ 80,900.00 - 129,725.00 annually. Actual salary offered to successful candidates will vary based on their skills and experience. Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.
Read the full posting
Work setting: Not stated
Employment: Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting

Lead development, deployment, and monitoring of predictive models for LTV, loss cost, pricing, and retention
Turn complex business problems into scalable analytical solutions with stakeholders
Build, validate, and maintain machine learning and statistical models
Deploy and operationalize models in Azure Machine Learning using MLOps practices
Present findings and recommendations to technical and non-technical audiences

From the employer’s posting

Lead the end-to-end development, deployment, and monitoring of predictive models supporting Lifetime Value (LTV), Loss Cost, pricing, retention, and profitability initiatives

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

Deploy and operationalize models using Azure Machine Learning and modern MLOps practices

Communicate analytical findings, model insights, and recommendations to technical and non-technical audiences

What you’ll bring

All qualifications

Core experience

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
Experience with MLOps, model governance, responsible AI practices, and production-scale machine learning solutions is considered a strong asset.
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.
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.

Qualification wording

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

Experience with MLOps, model governance, responsible AI practices, and production-scale machine learning solutions is considered a strong asset.

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.

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.

Apply at Allstate

Posting record

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Status in our records: Live
First seen by us: Sep 10, 202654 days ago
Recorded sightings: 164
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 54

Similar jobs usually come down between day 7 and day 55.

From 9,988 similar postings that came down. Coming down is not always a hire.

Allstate is hiring

15 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring at a steady pace
Takes jobs down quickly
7% of open jobs were reposted

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SAS
SQL
Azure

Where the posting names them

- 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.

Skills Analytics, Azure Machine Learning, Data Science, Machine Learning Algorithms, Machine Learning Model Development, Model Deployment, Python (Programming Language), Statistical Models, Structured Query Language (SQL) Compensation

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.

- 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 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.

- 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.

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Your next step

Complete your application on allstate.wd5.myworkdayjobs.com. The employer’s form will show what is required.

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Has Allstate posted this job before?

Yes. We’ve followed one other Data Scientist job there since April 2026. It came down after 9 days.

Place not statedCame down after 9 days, first seen Apr 18
This jobUp 55 days so far, first seen Sep 10

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025: $120,230
Expected change, 2025 to 2035: 34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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.

Job Description

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 www.allstate.ca. For safety tips and advice, visit www.goodhandsadvice.ca.

Through our Employee Value Proposition, we have worked hard to develop and nurture a culture where employees feel valued, experience personal growth, have career options and truly enjoy the work they do.

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 strong 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 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. If you require accommodation, please let us know and we will work with you to meet your needs.

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Skills

Analytics, Azure Machine Learning, Data Science, Machine Learning Algorithms, Machine Learning Model Development, Model Deployment, Python (Programming Language), Statistical Models, Structured Query Language (SQL)

Compensation

Expected compensation for this role ranges from $ 80,900.00 - 129,725.00 annually. Actual salary offered to successful candidates will vary based on their skills and experience.

Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.

Allstate Canada Group uses AI technology tools to assist in screening, selecting, assessing, and scheduling interviews with candidates as part of the recruitment process.

This job posting is for a current open role within the organization.

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