Data Scientist –

- Senior

Client: Ministry of Public and Business Service Delivery and Procurement

Job Title: RQ11452 –

- Data Scientist –
- Senior

Work Location: Toronto, Ontario – Onsite

Estimated Start Date: October 26, 2026

Estimated End Date: October 5, 2027

Business Days: 240

Extension: 125 days

Hours: 7.25 hours per day

Security Level: No Clearance Required

Role Overview

We are seeking an experienced Senior Data Scientist to analyze complex structured and unstructured datasets and develop predictive models, analytical frameworks, business intelligence solutions, and geospatial insights that support business planning, compliance, reporting, and evidence-based decision-making.

The successful candidate will have strong experience in data analytics, statistical analysis, machine learning, predictive modelling, SQL, Python/R, data management, data visualization, geospatial analysis, and business intelligence platforms such as Power BI, Tableau, R Shiny, or ArcGIS.

Key Responsibilities

- Data Science &
- Predictive Analytics
- Analyze complex datasets to generate predictive models, trends, patterns, and actionable insights.
- Apply statistical methods, machine learning, mathematics, and programming techniques to solve business problems.
- Develop creative statistical models and analytical frameworks to support business strategies and decision-making.
- Conduct exploratory and initial data analysis to understand data characteristics, patterns, relationships, and trends.
- Identify business problems and opportunities that can be addressed through data science and analytics.
- Develop data-driven solutions that improve business performance and decision-making.
- Apply pattern recognition and predictive modelling techniques to large and complex datasets.
- Data Management &
- Integration
- Identify relevant data sources and datasets required to address client business needs.
- Collect, integrate, transform, and analyze large structured, semi-structured, and unstructured datasets.
- Apply knowledge of data management, database architecture, data governance, metadata management, master data management, and data lineage.
- Support Extract, Transform, Load (ETL), data warehousing, and data integration activities.
- Work with historical, legacy, and modern datasets as part of data modernization and digitization initiatives.
- Support records conversion and data quality improvement initiatives.
- Use SQL to access, extract, transform, and analyze data across multiple platforms and repositories.
- Geospatial &
- Spatial Data Analytics
- Analyze and integrate spatial and non-spatial datasets to support planning, compliance, reporting, and decision-making.
- Apply geospatial analysis and spatial data management techniques to complex datasets.
- Develop analytical solutions incorporating geographic and spatial information.
- Communicate geospatial findings through maps, dashboards, reports, and presentations.
- Utilize tools such as ArcGIS or equivalent geospatial platforms.
- Data Visualization &
- Business Intelligence
- Develop dashboards, reports, and visualizations that communicate complex analytical findings.
- Utilize platforms such as Power BI, Tableau, R Shiny, ArcGIS, or equivalent analytics and visualization tools.
- Translate complex datasets and analytical results into clear, actionable business intelligence.
- Develop visual representations of trends, relationships, patterns, and geospatial insights.
- Support business stakeholders in interpreting analytical results and making informed decisions.
- Data Quality &
- Modernization




- Analyze datasets to identify duplicate records, inconsistencies, missing values, invalid data, and other quality issues.
- Support data migration, digitization, modernization, and information management initiatives.
- Conduct data quality assessments and recommend improvements.
- Validate data integrity, consistency, completeness, and accuracy.
- Support data transformation and integration across multiple systems and repositories.
- Work with structured, semi-structured, unstructured, historical, and legacy data environments.
- Research &
- Analytical Problem Solving
- Research, develop, and manage new information studies.
- Apply research methodologies and innovative analytical approaches to complex business challenges.
- Identify trends, relationships, correlations, and patterns within large datasets.
- Translate business and data requirements into analytical solutions.
- Integrate data from multiple sources and provide recommendations based on evidence and analytical findings.
- Apply emerging technologies, industry best practices, artificial intelligence, and machine learning techniques where appropriate.
- Collaboration &
- Communication
- Collaborate with business stakeholders, Information Management specialists, GIS specialists, Business Analysts, project teams, and technical resources.
- Communicate complex analytical findings effectively to both technical and non-technical audiences.
- Prepare technical documentation, business reports, data dictionaries, source-to-target mapping documents, and data flow diagrams.
- Present recommendations and analytical findings through reports, dashboards, maps, presentations, and other visualization formats.
- Facilitate discussions and support stakeholders in evidence-based decision-making.
- Work effectively within multidisciplinary teams and complex project environments.

Required Skills &

- Experience

Technical Knowledge & Skills – 50%

- Solid knowledge of information management, data management, database architecture, data governance, metadata management, master data management, and data lineage.
- Experience with ETL processes, data warehousing, and data integration.
- Knowledge of data modernization, digitization methodologies, records conversion, and data quality improvement practices.
- Experience managing structured, semi-structured, unstructured, historical, and legacy datasets.
- Strong proficiency in statistical analysis, data mining, predictive analytics, artificial intelligence, machine learning, research methodologies, and data modelling.
- Knowledge of relational databases and data analytics.
- Experience with geospatial analysis and spatial data management.
- Strong proficiency with SQL for accessing, extracting, transforming, and analyzing data.
- Strong proficiency with Python, R, or equivalent programming/data-analysis tools.
- Experience with Power BI, Tableau, R Shiny, ArcGIS, or equivalent analytical and visualization platforms.
- Knowledge of information management standards and data governance frameworks.
- Knowledge of accessibility requirements and applicable GO-ITS standards.
- Experience with Git or other code version control systems.
- Experience with database management systems.




- Awareness of emerging I⁢ trends and technologies.

Research, Analytical &
- Problem-Solving Skills – 40%

- Ability to analyze and assess complex datasets and identify data quality issues, including duplicates, inconsistencies, missing values, and invalid records.
- Ability to support data migration, digitization, modernization, and information management initiatives through data analysis and quality assessment.
- Ability to identify, assess, document, and translate business data requirements into analytical solutions.
- Ability to identify trends, patterns, relationships, and insights within large and complex datasets.
- Ability to analyze, integrate, and interpret both spatial and non-spatial datasets.
- Ability to develop and apply predictive models, analytical frameworks, business intelligence solutions, and geospatial analysis techniques.
- Ability to integrate data from multiple sources and provide recommendations supporting evidence-based decision-making.
- Ability to apply innovative analytical approaches, emerging technologies, and industry best practices to complex business challenges.
- Extensive experience with data mining, mathematics, statistical analysis, pattern recognition, and predictive modelling.
- Experience developing data-driven solutions to improve business performance and decision-making.

Communication &
- General Skills – 10%

- Excellent verbal and written communication skills.
- Ability to communicate complex analytical findings to technical and non-technical audiences.
- Ability to prepare technical documentation, business reports, data dictionaries, source-to-target mappings, and data flow diagrams.
- Strong collaboration skills with business, technical, GIS, Information Management, and project teams.
- Ability to communicate analytical and geospatial findings through dashboards, maps, reports, and presentations.
- Strong presentation, facilitation, and stakeholder engagement skills.
- Excellent analytical, problem-solving, and decision-making capabilities.
- Strong interpersonal and negotiation skills.
- Ability to work effectively in multidisciplinary and complex project environments.
- Proven ability to meet deadlines and work effectively as part of a team.

Desirable Skills
- Advanced degree in Social Science, Statistics, or a related discipline.
- Data Science Professional Certificate, such as the IBM Data Science Professional Certificate.
- Google Data Engineer certification or equivalent.
- Experience working with large-scale business datasets.
- Experience supporting Public Sector or Government data initiatives.
- Experience with advanced geospatial analytics and GIS platforms.
- Experience applying AI and machine learning to complex business problems.

Mandatory Documents
- Updated Resume in Word format –
- Mandatory
- References –
- Mandatory
- Expected Hourly Rate –
- Mandatory
- Visa Status –
- Mandatory
- LinkedIn ID –
- Mandatory

How to Apply If you are interested and your profile matches the requirements, please send the following mandatory documents to [email protected] by Tuesday, September 8, 2026, at 10:00 AM EST.

Applications without the mandatory documents cannot be processed or submitted.

If this opportunity is not suitable for you, please feel free to share it with qualified Senior Data Scientists with strong experience in Python/R, SQL, statistical analysis, machine learning, predictive modelling, Power BI/Tableau, geospatial analytics, data governance, ETL, data quality, and large-scale data environments.

📌 – Data Scientist – Senior (Toronto)
🏢 S M Software Solutions
📍 Toronto