Data Scientist

Aviva

Data Scientist driving fraud detection at Aviva Canada. Collaborating with various partners and developing ML models to protect customers and business through actionable insights.

Posted 7/14/2026full-timeMarkham • 🇨🇦 CanadaJuniorMid-Level💰 CA$80,000 - CA$120,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, developing, and deploying machine learning models and scalable code, with a strong focus on data-driven decision-making and effective communication of insights. Proficient in Python, SQL, and MLOps practices, ensuring high-quality code and adherence to software engineering best practices.

Highest-signal resume keywords

Machine Learning Model DevelopmentPython ProgrammingSQL ProficiencyMLOps PracticesData Engineering Best Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData AnalysisStatistical TechniquesCode OptimizationSoftware Engineering Best PracticesPattern RecognitionData Pipeline MaintenanceModel DeploymentVersion ControlETL Strategies

Soft Skills

Communication SkillsCollaboration Skills

Tools & Technologies

GitData WarehousingReal-Time APIs

Certifications & Qualifications

MSc in Computer ScienceMSc in EngineeringMSc in MathematicsMSc in StatisticsMSc in Physics

Industry Keywords

Data-Driven DecisionsProduction-Ready CodeEnd-to-End Model Development LifecycleComplex DatasetsIT StandardsEnterprise Architecture

Tech Stack

Tools & technologies

ETLPythonSQL

About the role

Key responsibilities & impact

Design, develop, test, and deploy scalable, production‑ready code and machine learning models.
Transform large, complex datasets into actionable insights, recommendations, and data‑driven decisions.
Develop innovative approaches to pattern recognition using machine learning, statistical, and analytical techniques.
Design and deploy models to real‑time APIs, ensuring reliability, performance, and scalability.
Communicate insights and model outcomes clearly to both technical and non‑technical audiences.
Maintain, enhance, and optimize existing codebases and data pipelines.
Drive delivery accountability for both project‑based initiatives and BAU work, aligned to agreed timelines and priorities.
Ensure solutions conform to IT and Enterprise Architecture standards where applicable.

Requirements

What you’ll need

MSc in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field (PhD preferred).
2+ years of experience across the end‑to‑end model development lifecycle, working with large and complex datasets (industry or academic/post‑doctoral experience considered).
2+ years of experience programming in Python, with a solid understanding of software engineering best practices (modularity, code reusability, version control, repositories).
Proficiency in SQL and Git, with hands‑on experience collaborating in shared codebases.
Experience productionizing machine learning models, including monitoring, maintenance, and MLOps practices.
Familiarity with data warehouse concepts, ETL strategies and data engineering best practices.
A strong track record of building robust, maintainable, high‑quality code.
Ability to operate optimally in a data‑driven software engineering environment and translate data into business value.
Strong communication and collaboration skills, with the ability to work across disciplines.

Benefits

Comp & perks

Compelling rewards package including base compensation, eligibility for annual bonus, retirement savings, share plan, health benefits, personal wellness, and volunteer opportunities.
Hybrid flexible work model.
Outstanding career development opportunities.
We’ll support your professional development education.
Competitive vacation package with the option to purchase 5 extra days off per year.
Employee-driven programs focused on gender, LGBTQ+, origins, diversity, and inclusion.
Corporate wellness programs to support our employees’ physical and mental health.