Data Scientist

TELUS

Data Scientist developing scalable data architectures and analytics solutions for TELUS's operations. Collaborating with stakeholders and stakeholders to drive business decisions through data insights.

Posted 7/21/2026full-timeBurnaby • 🇨🇦 CanadaMid-LevelSenior💰 CA$86,000 - CA$160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates advanced proficiency in Google Cloud Platform (GCP) and expertise in data architecture, ETL/ELT processes, and analytics solutions. Capable of leveraging AI and machine learning techniques to drive business insights and optimize data pipelines for performance and scalability.

Highest-signal resume keywords

Google Cloud Platform (GCP)BigQueryLooker StudioETL/ELT DesignPython

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ArchitectureData VisualizationSQLMachine LearningStatistical AnalysisExploratory Data AnalysisData ModelingDimensional DesignAI CapabilitiesCI/CD

Soft Skills

CommunicationMentoringCollaboration

Tools & Technologies

PulumiYAMLGitHubVertex AICloud SchedulerDataprocBatch Jobs

Certifications & Qualifications

Master's Degree in Computer ScienceMaster's Degree in Data ScienceMaster's Degree in StatisticsMaster's Degree in EngineeringPhD in Relevant Field

Industry Keywords

Data GovernanceData PipelinesAnalytics SolutionsBusiness InsightsReal-Time Analytics

Tech Stack

Tools & technologies

BigQueryCloudETLGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Design and build robust data pipelines and architectures on Google Cloud Platform (GCP), leveraging BigQuery, Workflows, Cloud Scheduler, Dataproc, and Batch jobs
Establish scalable ETL/ELT processes that efficiently ingest, transform, and prepare data from diverse sources for analytics and reporting
Build and manage GCP resources using Pulumi and YAML configurations, and maintain code in GitHub
Conduct in-depth exploratory data analysis and apply statistical methods, machine learning techniques, and AI-driven analytics to uncover patterns, trends, and actionable business insights
Develop analytical models and leverage AI capabilities to support strategic decision-making and operational improvements across key business metrics
Design and build intuitive, visually compelling dashboards and reports in Looker Studio that communicate complex data stories to diverse stakeholders
Create data visualizations with a strong eye for clarity, aesthetics, and user experience that enable self-service analytics
Leverage GCP's data ecosystem (BigQuery, Workflows, Cloud Scheduler, Dataproc, Batch, and Vertex AI) to optimize query performance, reduce costs, and enable real-time analytics
Implement best practices for data governance, security, and scalability within GCP environments
Work with business teams and stakeholders to understand data requirements and translate business questions into analytical solutions
Document analytical findings and architectural decisions clearly, and mentor team members on data best practices.

Requirements

What you’ll need

Master's degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative discipline — or a PhD in a relevant field
3+ years of experience designing and implementing data architectures and analytics solutions in production environments, delivering measurable business impact
Advanced proficiency in Google Cloud Platform (GCP), with hands-on experience in BigQuery, Workflows, Cloud Scheduler, Dataproc, and Batch jobs
Expert-level experience with Looker Studio for creating dashboards, reports, and data visualizations that drive business insights and support decision-making
Strong foundation in data architecture and ETL/ELT design, with the ability to optimize data pipelines for performance, scalability, and cost efficiency
Demonstrated expertise in data visualization and analytics, with a keen eye for designing clear, compelling, and actionable insights that resonate with both technical and business audiences
Experience working in GitHub, building and managing GCP resources using Pulumi and YAML configurations
Strong SQL skills and experience working with large-scale datasets; proficiency in data modeling and dimensional design
Proven experience analyzing structured and unstructured data using statistical methods, exploratory data analysis, and machine learning techniques to drive insights
Proficiency in Python or similar languages for data processing and analytics
Experience leveraging AI capabilities and tools (such as Vertex AI) to build machine learning models and AI solutions that enhance analytical capabilities
Experience deploying and monitoring data solutions in production, with familiarity in CI/CD, version control, and cloud infrastructure best practices
Strong ability to translate business questions into analytical frameworks and communicate findings effectively with both technical and non-technical stakeholders.

Benefits

Comp & perks

Comprehensive total rewards package highlighting competitive salary and bonus structures
Minimum 3 weeks of vacation
Flexible benefits plan to meet the needs of you and your family
Flexibility to work in-office, virtually or a combination of both
Generous company matched pension and share purchase programs
Opportunity to give back to communities in which we work, live and serve
Career growth and learning & development opportunities to develop your skills
And much more …