Aviva Canada
Insurance
DataScientist
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Scientist at Aviva Canada. Skills: Machine Learning, Data Pipelines, Python, SQL. Design, develop, test, deploy code. Design, develop, test, deploy machine learning models”
What You'll Achieve.
protect customers and the business; real-world applications at scale; business value
Industry & Context.
translate data into business value; problem solving
What They're Looking For.
Must Have
MSc in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field, 2+ years of experience across the end-end model development lifecycle, 2+ years of experience programming in Python, solid understanding of software engineering best practices, Proficiency in SQL, Proficiency in Git, hands-on experience collaborating in shared codebases, Experience productionizing machine learning models, monitoring, maintenance, MLOps practices, Familiarity with data warehouse concepts, ETL strategies, data engineering best practices, track record of building robust, maintainable, high-quality code, Ability to operate optimally in a data-driven software engineering environment, translate data into business value, communication and collaboration skills, ability to work across disciplines
Nice to Have
PhD preferred, Experience working with cloud-based data platforms and technologies, PostgreSQL, Teradata, Hadoop, AWS, Experience with CI/CD pipelines, modern deployment practices, Exposure to fraud, insurance, or highly regulated domains, Hands-on experience building and consuming APIs, creative, curious, and resourceful approach to problem solving
What You'll Do.
deploy machine learning models
Transform large datasets
Develop innovative approaches
Design and deploy models
Communicate model outcomes
Maintain data pipelines
Enhance data pipelines
Optimize data pipelines
Drive delivery accountability
Ensure solutions conform
How You'll Work.
Team & Collaboration
work closely with business partners; work across disciplines
Communication Scope
Communicate insights clearly; Communicate model outcomes clearly; communication skills; collaboration skills
Process & Methodology
Drive delivery accountability for project-based initiatives, Drive delivery accountability for BAU work
Full Job Description
## **Experience Aviva** **Together, we are Aviva.** Our values — Care, Commitment, Community, and Confidence — guide how we show up for each other and for our customers. Individually, they’re words. Together, they define who we are. At**Aviva Canada** , we put people first, our employees, our customers, and our communities. We’re proud of a culture built on care, inclusion, and collaboration, where your voice matters and your growth is supported. We’re not just about insurance; we’re about making a real difference by protecting what matters most. ## **The Opportunity** Join an exciting team of data scientists and engineers at the forefront of using data to drive decisions at every level of our organization. The insurance industry is undergoing a transformation and you get to be in the driver’s seat of this data-driven, technology revolution. As a **Data Scientist** on the **Fraud Data Science team** , you’ll work closely with a wide range of business partners and help shape future products and solutions. You’ll contribute to high‑impact initiatives focused on fraud detection, using machine‑learning‑based solutions to protect customers and the business. You’ll be involved across the full development lifecycle, from idea generation and experimentation through deployment, monitoring, and ongoing support. Your work will include building and deploying data pipelines, machine learning, and statistical models used in real‑world applications at scale. The team’s models are already running in production, and you’ll help expand and evolve these capabilities as part of our ongoing InsurTech transformation. ## **What you’ll do:** * 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 re
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