We are seeking a highly accomplished Data Analyst III for an enterprise-level contract opportunity based in Toronto. In this role, you will take on a premier data science, advanced analytics, and business intelligence capacity, specializing in designing and delivering end-to-end analytical solutions, predictive modeling, and scalable decision-support tools.
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Operating within a hybrid model in Toronto, you will bridge the gap between complex datasets, machine learning frameworks, and executive decision-makers. You will apply statistical analysis, data-driven experimentation, and machine learning to address intricate business challenges, while translating quantitative insights into intuitive, executive-ready Power BI dashboards. This position demands an analytical authority with extensive hands-on expertise in Python, advanced SQL, cloud-based AI/ML platforms (Azure, AWS, or GCP), and data visualization who thrives in fast-paced environments and can operationalize insights that drive measurable business impact.
Location: Toronto, ON
Assignment Type: Hybrid (4 days onsite per week)
Contract Duration: 12-month contract (with potential for extension and permanent conversion)
Advantages
High-Impact Scope: Combine data science, machine learning experimentation, and executive-level business intelligence within one role.
Modern Cloud & AI Stack: Work hands-on with Python, PySpark, Power BI, and leading cloud platforms (Azure, AWS, or GCP).
Enterprise Stability & Growth: 12-month engagement with strong potential for contract extension and permanent conversion.
Collaborative Environment: Partner with cross-functional teams and senior leaders across a leading enterprise organization.
Responsibilities
Apply statistical analysis, machine learning algorithms, and advanced analytics techniques to identify emerging trends, systemic risks, and optimization opportunities.
Design, build, and deploy analytical models, experimentation frameworks, and data-driven solutions to solve complex business challenges.
Develop and maintain curated datasets, feature engineering layers, and analytical data models supporting both advanced modeling and BI reporting streams.
Translate ambiguous business questions into structured quantitative approaches, key performance indicators (KPIs), and measurable delivery outcomes.
Design, build, and deploy interactive Power BI dashboards, automated reporting solutions, and executive-ready data storytelling presentations.
Partner with cross-functional stakeholders to define business requirements, establish analytical roadmaps, and build data-driven decision frameworks.
Implement robust data quality checks, reconciliation routines, validation scripts, and data governance practices across model inputs and BI assets.
Operationalize analytics workflows by engineering automated data pipelines, continuous performance monitoring solutions, and repeatable reporting mechanisms.
Continuously refine and modernize analytical methodologies, predictive techniques, and reporting efficiencies.
Support enterprise risk, control, and compliance objectives through proactive analytical monitoring and actionable insight generation.
Qualifications
Core Data Analytics & Technical Requirements
Professional Experience: 5 to 7 years of dedicated experience in data analysis, advanced analytics, or data science delivering data-driven solutions with large datasets.
Python Mastery: Strong hands-on proficiency in Python and its core data and ML ecosystem, including Pandas, NumPy, Scikit-learn, PySpark, and deep learning libraries (TensorFlow or PyTorch).
Advanced SQL: Proven expertise writing complex SQL queries, stored procedures, joins, and data extraction routines across enterprise relational and analytical databases.
Cloud AI/ML Platforms: Demonstrated experience working with cloud-based data and AI/ML platforms (such as Microsoft Azure, AWS, or GCP), including managing data workflows or models in production environments.
Business Intelligence & Visualization: Extensive experience designing, building, and deploying impactful, user-centric visualizations, semantic models, and interactive dashboards in Microsoft Power BI.
Education: Undergraduate degree or advanced technical degree preferred (such as Mathematics, Physics, Computer Science, Engineering, Finance, or a related discipline).
Preferred Technical Assets
Tableau: Hands-on proficiency with Tableau for reporting and visual analytics is considered an asset.
Machine Learning Lifecycle: Practical experience with supervised and unsupervised learning, model explainability, feature engineering pipelines, hyperparameter tuning, and causal inference.
Soft Skills & Delivery Attributes
Execution & Organizational Skills: Outstanding organizational discipline with the ability to manage competing priorities, deliver with speed, and execute within fast-paced environments.
Navigating Ambiguity: Proven ability to break down ambiguous business problems into structured, solvable analytical workflows.
Stakeholder Management: Exceptional interpersonal and communication skills to influence, align, and present insights effectively across multidisciplinary teams and business stakeholders.
Risk Acumen: Strong risk awareness and proactive mindset to challenge assumptions, safeguard data integrity, and identify potential operational risks.
Summary
If you're interested in the "Data Analyst III" role based in Toronto, we encourage you to apply online at www.randstad.ca.
Only qualified candidates will be contacted for the next steps. We look forward to hearing from you!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
show more
We are seeking a highly accomplished Data Analyst III for an enterprise-level contract opportunity based in Toronto. In this role, you will take on a premier data science, advanced analytics, and business intelligence capacity, specializing in designing and delivering end-to-end analytical solutions, predictive modeling, and scalable decision-support tools.
Operating within a hybrid model in Toronto, you will bridge the gap between complex datasets, machine learning frameworks, and executive decision-makers. You will apply statistical analysis, data-driven experimentation, and machine learning to address intricate business challenges, while translating quantitative insights into intuitive, executive-ready Power BI dashboards. This position demands an analytical authority with extensive hands-on expertise in Python, advanced SQL, cloud-based AI/ML platforms (Azure, AWS, or GCP), and data visualization who thrives in fast-paced environments and can operationalize insights that drive measurable business impact.
Location: Toronto, ON
Assignment Type: Hybrid (4 days onsite per week)
Contract Duration: 12-month contract (with potential for extension and permanent conversion)
...
Advantages
High-Impact Scope: Combine data science, machine learning experimentation, and executive-level business intelligence within one role.
Modern Cloud & AI Stack: Work hands-on with Python, PySpark, Power BI, and leading cloud platforms (Azure, AWS, or GCP).
Enterprise Stability & Growth: 12-month engagement with strong potential for contract extension and permanent conversion.
Collaborative Environment: Partner with cross-functional teams and senior leaders across a leading enterprise organization.
Responsibilities
Apply statistical analysis, machine learning algorithms, and advanced analytics techniques to identify emerging trends, systemic risks, and optimization opportunities.
Design, build, and deploy analytical models, experimentation frameworks, and data-driven solutions to solve complex business challenges.
Develop and maintain curated datasets, feature engineering layers, and analytical data models supporting both advanced modeling and BI reporting streams.
Translate ambiguous business questions into structured quantitative approaches, key performance indicators (KPIs), and measurable delivery outcomes.
Design, build, and deploy interactive Power BI dashboards, automated reporting solutions, and executive-ready data storytelling presentations.
Partner with cross-functional stakeholders to define business requirements, establish analytical roadmaps, and build data-driven decision frameworks.
Implement robust data quality checks, reconciliation routines, validation scripts, and data governance practices across model inputs and BI assets.
Operationalize analytics workflows by engineering automated data pipelines, continuous performance monitoring solutions, and repeatable reporting mechanisms.
Continuously refine and modernize analytical methodologies, predictive techniques, and reporting efficiencies.
Support enterprise risk, control, and compliance objectives through proactive analytical monitoring and actionable insight generation.
Qualifications
Core Data Analytics & Technical Requirements
Professional Experience: 5 to 7 years of dedicated experience in data analysis, advanced analytics, or data science delivering data-driven solutions with large datasets.
Python Mastery: Strong hands-on proficiency in Python and its core data and ML ecosystem, including Pandas, NumPy, Scikit-learn, PySpark, and deep learning libraries (TensorFlow or PyTorch).
Advanced SQL: Proven expertise writing complex SQL queries, stored procedures, joins, and data extraction routines across enterprise relational and analytical databases.
Cloud AI/ML Platforms: Demonstrated experience working with cloud-based data and AI/ML platforms (such as Microsoft Azure, AWS, or GCP), including managing data workflows or models in production environments.
Business Intelligence & Visualization: Extensive experience designing, building, and deploying impactful, user-centric visualizations, semantic models, and interactive dashboards in Microsoft Power BI.
Education: Undergraduate degree or advanced technical degree preferred (such as Mathematics, Physics, Computer Science, Engineering, Finance, or a related discipline).
Preferred Technical Assets
Tableau: Hands-on proficiency with Tableau for reporting and visual analytics is considered an asset.
Machine Learning Lifecycle: Practical experience with supervised and unsupervised learning, model explainability, feature engineering pipelines, hyperparameter tuning, and causal inference.
Soft Skills & Delivery Attributes
Execution & Organizational Skills: Outstanding organizational discipline with the ability to manage competing priorities, deliver with speed, and execute within fast-paced environments.
Navigating Ambiguity: Proven ability to break down ambiguous business problems into structured, solvable analytical workflows.
Stakeholder Management: Exceptional interpersonal and communication skills to influence, align, and present insights effectively across multidisciplinary teams and business stakeholders.
Risk Acumen: Strong risk awareness and proactive mindset to challenge assumptions, safeguard data integrity, and identify potential operational risks.
Summary
If you're interested in the "Data Analyst III" role based in Toronto, we encourage you to apply online at www.randstad.ca.
Only qualified candidates will be contacted for the next steps. We look forward to hearing from you!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
show more
