Pricing Data Scientist, CoE – Personal Lines (Hybrid)

Aviva; Markham; Hybrid; CAD 75,000 - 95,000; Full time

Job summary

A leading insurance provider in York Region, Markham, is seeking a skilled data scientist to join their Personal Lines Pricing team. This role involves transforming complex datasets into actionable insights, participating in MLOps, and collaborating with stakeholders to enhance pricing solutions. Candidates should possess a university degree in a relevant field and strong skills in data analysis, Python programming, and communication. The company offers a competitive rewards package and a hybrid working model.

Benefits

Base compensation

Annual bonus eligibility

Retirement savings plan

Health benefits

Professional development support

Competitive vacation package

Qualifications

• 3+ years of experience in model development and working with large datasets.
• Strong analytical skills with a keen interest in insurance pricing.
• Proficiency in Python and best practices in software engineering.

Responsibilities

• Transform complex datasets into actionable insights and recommendations.
• Participate in all phases of the MLOps pricing model lifecycle.
• Collaborate with business and engineering partners.

Skills

Data analysis

Model development

Communication skills

Python programming

Analytical skills

Collaboration

MLOps

Bilingual in French and English

Education

University degree in data science or related field

Master's degree (asset)

Tools

Cloud platforms

CI/CD tools

Job description

A leading insurance provider in York Region, Markham, is seeking a skilled data scientist to join their Personal Lines Pricing team. This role involves transforming complex datasets into actionable insights, participating in MLOps, and collaborating with stakeholders to enhance pricing solutions. Candidates should possess a university degree in a relevant field and strong skills in data analysis, Python programming, and communication. The company offers a competitive rewards package and a hybrid working model.