We are seeking a highly accomplished Senior Data Scientist for an enterprise-level contract opportunity based in Toronto. In this role, you will take on a premier statistical modeling, geospatial analysis, and predictive analytics capacity, specializing in researching, developing, and deploying innovative machine learning models and business intelligence solutions.
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As a senior data scientist, you will bridge the gap between complex spatial and non-spatial datasets, advanced statistical programming, and strategic business decision-making. Operating fully onsite in Toronto, you will lead full-lifecycle analytics initiatives—mining large structured and unstructured datasets, cleaning and modeling relational data, building interactive visualization dashboards, and establishing predictive frameworks to support compliance, planning, and reporting objectives.
Location: Toronto, ON
Assignment Type: Onsite (5 days per week)
Contract Duration: 11-month contract (with potential for extension)
Advantages
Geospatial & Predictive Depth: Combine machine learning models with spatial data analysis using platforms like ArcGIS, R Shiny, Python, and R.
Full Data Lifecycle Ownership: Drive end-to-end analytics initiatives spanning ETL, data quality remediation, predictive modeling, and executive reporting.
Modern Visualization Stack: Construct high-impact business intelligence solutions and dashboards utilizing Power BI, Tableau, and interactive mapping frameworks.
Cross-Functional Influence: Translate complex statistical modeling and AI/ML insights into actionable strategies for cross-functional leadership teams.
Responsibilities
Analyze complex spatial and non-spatial datasets to build predictive models, statistical frameworks, and actionable business insights.
Apply statistical methods, machine learning algorithms, and programming languages (Python, R, SQL) to interpret trends and support data-driven strategies.
Initiate, research, develop, and manage new analytical studies, devising innovative statistical models and algorithms.
Perform initial data exploration to understand data characteristics, assess quality issues, and identify underlying patterns.
Extract, transform, and integrate large structured, semi-structured, and unstructured datasets from multiple relational databases and enterprise repositories.
Design and deploy interactive analytics and visualization dashboards using Power BI, Tableau, R Shiny, ArcGIS, or equivalent tools.
Develop source-to-target mappings, data dictionaries, ETL pipelines, and data flow diagrams to support data modernization and digitization efforts.
Collaborate with business analysts, GIS specialists, and technical leads to translate business requirements into advanced analytical solutions.
Prepare comprehensive technical documentation, analytical reports, data models, and executive presentations.
Ensure data analytics solutions conform to enterprise information management standards, data governance frameworks, and accessibility guidelines.
Qualifications
Core Technical & Analytical Requirements
Data Science & Machine Learning: Extensive hands-on experience in statistical analysis, pattern recognition, data mining, predictive modeling, artificial intelligence, and machine learning techniques.
Programming & SQL Proficiency: Strong hands-on experience using Python, R, and complex SQL queries for data transformation, automation, and statistical modeling.
Geospatial & Spatial Analytics: Demonstrated proficiency analyzing, integrating, and interpreting both spatial and non-spatial datasets using ArcGIS, R Shiny, or equivalent spatial analysis tools.
BI & Visualization Tools: Hands-on experience developing business intelligence dashboards and reports using Power BI, Tableau, R Shiny, or similar reporting platforms.
Data Management & ETL: Deep knowledge of relational databases, database architecture, metadata management, data warehousing, data quality assessment, and ETL processes.
Version Control & Methods: Experience using Git for code version control, alongside familiarity with structured SDLC and project management methodologies.
Preferred Assets
Advanced Education: An advanced degree (Master's or Ph.D.) in Social Sciences, Statistics, Data Science, Mathematics, or a related quantitative field.
Professional Certifications: Industry certifications such as IBM Data Science Professional Certificate or Google Cloud Data Engineer certification.
Soft Skills & Professional Attributes
Communication & Visualization: Exceptional verbal and written communication skills, with proven ability to present complex statistical and geospatial findings clearly to non-technical stakeholders.
Problem Solving & Collaboration: Outstanding analytical, decision-making, and interpersonal skills to collaborate effectively within multi-disciplinary project teams.
Summary
If you're interested in the "Senior Data Scientist" 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 Senior Data Scientist for an enterprise-level contract opportunity based in Toronto. In this role, you will take on a premier statistical modeling, geospatial analysis, and predictive analytics capacity, specializing in researching, developing, and deploying innovative machine learning models and business intelligence solutions.
As a senior data scientist, you will bridge the gap between complex spatial and non-spatial datasets, advanced statistical programming, and strategic business decision-making. Operating fully onsite in Toronto, you will lead full-lifecycle analytics initiatives—mining large structured and unstructured datasets, cleaning and modeling relational data, building interactive visualization dashboards, and establishing predictive frameworks to support compliance, planning, and reporting objectives.
Location: Toronto, ON
Assignment Type: Onsite (5 days per week)
Contract Duration: 11-month contract (with potential for extension)
Advantages
Geospatial & Predictive Depth: Combine machine learning models with spatial data analysis using platforms like ArcGIS, R Shiny, Python, and R.
...
Full Data Lifecycle Ownership: Drive end-to-end analytics initiatives spanning ETL, data quality remediation, predictive modeling, and executive reporting.
Modern Visualization Stack: Construct high-impact business intelligence solutions and dashboards utilizing Power BI, Tableau, and interactive mapping frameworks.
Cross-Functional Influence: Translate complex statistical modeling and AI/ML insights into actionable strategies for cross-functional leadership teams.
Responsibilities
Analyze complex spatial and non-spatial datasets to build predictive models, statistical frameworks, and actionable business insights.
Apply statistical methods, machine learning algorithms, and programming languages (Python, R, SQL) to interpret trends and support data-driven strategies.
Initiate, research, develop, and manage new analytical studies, devising innovative statistical models and algorithms.
Perform initial data exploration to understand data characteristics, assess quality issues, and identify underlying patterns.
Extract, transform, and integrate large structured, semi-structured, and unstructured datasets from multiple relational databases and enterprise repositories.
Design and deploy interactive analytics and visualization dashboards using Power BI, Tableau, R Shiny, ArcGIS, or equivalent tools.
Develop source-to-target mappings, data dictionaries, ETL pipelines, and data flow diagrams to support data modernization and digitization efforts.
Collaborate with business analysts, GIS specialists, and technical leads to translate business requirements into advanced analytical solutions.
Prepare comprehensive technical documentation, analytical reports, data models, and executive presentations.
Ensure data analytics solutions conform to enterprise information management standards, data governance frameworks, and accessibility guidelines.
Qualifications
Core Technical & Analytical Requirements
Data Science & Machine Learning: Extensive hands-on experience in statistical analysis, pattern recognition, data mining, predictive modeling, artificial intelligence, and machine learning techniques.
Programming & SQL Proficiency: Strong hands-on experience using Python, R, and complex SQL queries for data transformation, automation, and statistical modeling.
Geospatial & Spatial Analytics: Demonstrated proficiency analyzing, integrating, and interpreting both spatial and non-spatial datasets using ArcGIS, R Shiny, or equivalent spatial analysis tools.
BI & Visualization Tools: Hands-on experience developing business intelligence dashboards and reports using Power BI, Tableau, R Shiny, or similar reporting platforms.
Data Management & ETL: Deep knowledge of relational databases, database architecture, metadata management, data warehousing, data quality assessment, and ETL processes.
Version Control & Methods: Experience using Git for code version control, alongside familiarity with structured SDLC and project management methodologies.
Preferred Assets
Advanced Education: An advanced degree (Master's or Ph.D.) in Social Sciences, Statistics, Data Science, Mathematics, or a related quantitative field.
Professional Certifications: Industry certifications such as IBM Data Science Professional Certificate or Google Cloud Data Engineer certification.
Soft Skills & Professional Attributes
Communication & Visualization: Exceptional verbal and written communication skills, with proven ability to present complex statistical and geospatial findings clearly to non-technical stakeholders.
Problem Solving & Collaboration: Outstanding analytical, decision-making, and interpersonal skills to collaborate effectively within multi-disciplinary project teams.
Summary
If you're interested in the "Senior Data Scientist" 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
