Intact Financial (HK) Limited (Intact Lab) is the first Asia Pacific Region expansion of Intact Financial Corporation, Canada’s largest home, auto and business insurance company (TSX : IFC, HK$120 billion in market cap).
This is an exciting chapter of our journey to become the best insurance A.I. shop in the world.
Did you know that one in five Canadians count on us to protect what matters to them most? At the Intact Lab, that keeps us busy.
Very busy. As our company’s innovation hub, we get to spend our days reimagining the insurance experience through data sciences, product management and design.
Life in the Lab
The Intact Lab’s mission is to develop and implement innovative data science (ML / AI) solutions that contribute to the realization of Intact’s strategic goals.
Every day, you’ll inspire and be inspired by the brilliant minds of our greater lab team : actuaries, data scientists, machine learning experts, geomathematicians, meteorologists, software engineers and designers.
Together, you will tackle challenging problems and bring innovative solutions to life.
As our company grows, your career will grow with it. There will always be an opportunity to learn new skills, develop your expertise or take your work in a new direction.
In this role, you will
Develop innovative solutions for trend recognition using machine learning and advanced statistics
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 on the findings
Collaborate with our teams in HK & Canada to share knowledge, learnings, results, and tools
Currently enrolled in a post-secondary degree in relevant disciplines (mathematics, science, engineering, operational research, economics, statistics, AI, computer science or a related field)
Experience in data science (ML / AI, or other relevant experience) is an asset
Multi-platform production experience with the following commercial and open-source data mining frameworks :
Open-source frameworks : R, Python, GitHub
Understanding of the underlying theory of machine learning
Understanding of either computer image analysis, natural language processing or artificial intelligence
Proficiency in applied analytical techniques, including regression analysis, clustering, decision tress, neural networks, SVM, collaborative filtering, k-nearest neighbour, association rules, and other machine learning techniques
Understanding of algorithmic complexity and scaling of execution times and use of memory with large datasets
Excellent communication, organization and a collaborative attitude
Creative thinking approach to vaguely defined ideas