Senior Data Scientist - Personal Lines Datahub

Pay at Intact is about much more than just salary.

• Flexible work arrangements and a hybrid work model

• Possibility to purchase up to 5 extra days off per year

• Multiple benefits offered to support physical and mental wellbeing, including telemedicine, Wellness account and much more

• Share plan & other savings: up to 12% of salary or even more (ask how you could earn guaranteed income for life)

Salary range (but not limited to):

118,700 - 145,100

Annual bonus target, based on the base salary, with a potential payout of up to double the target (subject to personal and company performance):

12%

As part of our commitment to Win As A Team, we share our success with employees through our annual bonus plan and Employee Share Purchase Plan (ESPP) – with Intact matching 50% of your net shares.

Our pension offerings provide flexibility and long-term security for our employees beyond their careers. We are one of the few companies offering the opportunity to receive guaranteed income for life via our defined benefit pension plan.

Salary for the candidate will be determined taking into consideration a number of factors including: experience, skills, qualifications, anticipated contribution to role, internal equity, etc. The salary range presented above is based on a 35-hour workweek and would represent a majority of different candidate profiles. However, we encourage candidates who may fall outside of this range to apply as well.

About the role

What is the Personal Lines Datahub (PLDH) team doing:

With the advent of generative AI and with AI becoming more of a commodity in general, most organizations now realize the importance of data and how being serious and diligent around data will translate into competitive advantages. The PLDH team, along other data platform teams in the lab, was created as part of this data strategical shift.

The team’s mandate is to ingest and curate AI-ready data products for AI in PL, with the ambition to expand usage to other teams outside of AI PL/lab in the future. We make data AI-ready.

Currently the team consists of data engineers, DevOps and Data Solutions Architects and would benefit from having a Data Scientist working closely with the technical PO, DS manager, and Data Engineering manager to ensure product-market fit and user-centric design (i.e. bringing DS insight into the mix)

In 2025 the team has worked on ingesting various data sources onto our Enterprise Data Platform. In 2026 the focus has shifted towards developing Client Journey Database (CJDB), our first data product, which aims at providing a 360 degree view of customer interactions.

What you'll do here:

• Play a key role in shaping the vision of CJDB, interacting with various stakeholders consisting of senior ICs and managers of other product teams.
• Work towards making CJDB and the Enterprise Data Catalog accessible by AI agents.
• Promote a data-centric culture in the lab and across IFC, spreading awareness around data products, platforms and tools.
• Pursue various data engineering and IA engineering challenges. The responsibilities of this role fall outside “typical data science work”. We therefore need a candidate who is enthusiastic about taking on new challenges and expanding their skillset, knowing they would not be doing core data science.
• Develop user-friendly tools and data products.
• Transform complex databases into relevant conclusions and recommendations.
• Keep pace with new approaches and trends and use them in your own solutions.
• Help maintain our data mining tools and platforms.
• Make actionable recommendations based user feedback.
• Work with other departments to promote the adoption of data governance principles.
• Validate the quality of the analytical approach and project outputs of the other team members.

What you bring to the table:

• Master’s degree in a relevant discipline (mathematics, science, engineering, operational research, economics, statistics, AI, computer science or a related field), or any combination of equivalent education and experience.
• At least 5 years of experience in the field of advanced statistics, data mining and text mining.
• Multi-platform production experience with the following commercial and open-source data mining frameworks: Open-source frameworks: R, Python, GitHub.
• Expert-level understanding of the underlying theory of machine learning.
• Expert-level understanding in either computer image analysis, natural language processing or artificial intelligence.
• Enthusiasm for teamwork.
• Can focus on vaguely defined issues requiring the application of a creative approach.
• Strong communication, time management and work organization skills.
• Bilingual (French and English): Need to interact on a regular basis with an English-speaking clientele and colleagues across the country.
• No Canadian work experience required however must be eligible to work in Canada.

#LI-Hybrid

Il s'agit d'un nouveau rôle au sein de notre équipe en pleine croissance | This role is a new member of our growing team.