Data Scientist, Growth – 12 Month Contract

EQ Bank | Equitable Bank

. Lead machine learning model development for growth initiatives, including pricing, customer engagement, recommendation systems, propensity modelling, net promoter score, and related decisioning use cases .

Posted 10/23/2026contractToronto • CanadaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in machine learning model development, including design, deployment, and monitoring of scalable solutions. Proficient in data engineering practices and experimental design, with strong communication skills to convey insights to diverse stakeholders.

Highest-signal resume keywords

Machine Learning Model DevelopmentPython ProgrammingGoogle Cloud PlatformExperimental DesignData Pipeline Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical AnalysisFeature EngineeringModel ValidationA/B TestingCausal InferenceData ProcessingModel DeploymentPerformance MonitoringAutomated Testing

Soft Skills

Analytical Problem-SolvingCommunicationMentoringIndependent WorkTime Management

Tools & Technologies

Google Cloud PlatformMicrosoft AzureMicrosoft FabricAmazon Web ServicesGitDockerVertex AISpark

Industry Keywords

Data ScienceAdvanced AnalyticsCustomer EngagementRecommendation SystemsPricing StrategiesRetention Strategies

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformPythonSparkSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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