Data Scientist driving analytics and experiments for Jerry.ai’s AI - powered advisor for cars, homes, and other physical assets. Embedded across growth, product, AI, or strategic partnerships.
About the role
- Data Scientist advancing machine learning for EQ Bank’s digital banking and growth initiatives. Building production models for pricing, personalization, experimentation, and customer engagement.
Responsibilities
- Lead machine learning model development for growth initiatives, including pricing, customer engagement, recommendation systems, propensity modelling, net promoter score, and related decisioning use cases
- Design and maintain scalable data pipelines, feature engineering frameworks, and workflows for model training, scoring, monitoring, backtesting, and reporting
- Develop and evaluate experimentation frameworks, including A/B testing, holdout analysis, uplift measurement, causal inference, and incrementality measurement
- Perform feature engineering, model selection, validation, calibration, and performance monitoring
- Partner with product, engineering, analytics, marketing, and business teams to define success measures, prioritize opportunities, and operationalize model outputs
- Lead or contribute to migration and modernization of models, analytical assets, pipelines, and workflows, including the transition from Microsoft Fabric and Azure to Google Cloud Platform
- Assess model dependencies and recommend whether assets should be migrated, refactored, rebuilt, consolidated, or retired
- Design production-ready machine learning solutions, including deployment pipelines, automated retraining, monitoring, and performance tracking
- Apply software engineering, data engineering, and machine learning operations practices, including modular design, version control, testing, automation, reproducibility, documentation, and code quality
- Validate migrated or rebuilt solutions by reconciling data, features, model results, and business outputs
- Communicate model and experiment findings to technical and non-technical stakeholders
- Create reusable analytical frameworks, shared code libraries, notebooks, and production-ready assets
- Mentor team members and support knowledge transfer and analytical excellence
Requirements
- Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Engineering, or a related quantitative field
- Six or more years of total experience in data science, machine learning, advanced analytics, or a closely related discipline
- Strong proficiency in Python, Structured Query Language, statistical analysis, Spark or similar distributed technologies, and scalable data processing
- Experience building, validating, deploying, monitoring, and governing machine learning models in production or production-adjacent environments
- Strong understanding of experimental design, hypothesis testing, causal inference, and measurement frameworks
- Experience with cloud analytical environments such as Google Cloud Platform, Microsoft Azure, Microsoft Fabric, Amazon Web Services, or similar platforms
- Working knowledge of Git-based development, code review, automated testing, dependency management, and continuous integration and deployment
- Experience with customer growth, personalization, pricing, recommendation systems, retention, or similar business applications
- Advanced analytical problem-solving and sound judgment in ambiguous situations
- Ability to explain technical information, trade-offs, migration risks, and insights to technical and non-technical audiences
- Ability to work independently, manage multiple priorities, and deliver high-quality work in a fast-paced environment
- Preferred: experience with cloud migrations, Vertex AI or equivalent capabilities, modern machine learning platforms, Docker, infrastructure as code, observability, orchestration, and automated retraining
- All candidates considered for hire must successfully complete a criminal background check and credit check
Benefits
- Competitive discretionary bonus
- Market leading RRSP match program
- Medical, dental, vision, life, and disability benefits
- Employee Share Purchase Plan
- Maternity/Parental top-up while you care for your little one
- Generous vacation policy and personal days
- Virtual events to connect with your fellow colleagues
- Professional development and comprehensive Career Development program
- Hybrid work arrangement
- Barrier-free recruitment process and work environment
- Criminal background check and credit check for candidates considered for hire
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