Client: Community Services Cluster
Ministry: Ministry of Public and Business Service Delivery and Procurement
Location: Toronto, Ontario – 56 Wellesley Street
Work Arrangement: 100% Onsite (5 Days per Week)
Contract Start Date: October 26, 2026
Contract End Date: October 5, 2027
Extension: Up to 125 business days (1 extension option), subject to client approval and Master Service Agreement extension
Security Clearance: No Clearance Required
Overview
Our client, the Community Services Cluster within the Ministry of Public and Business Service Delivery and Procurement, is seeking two experienced
Senior Data Scientists to support complex data analytics, modernization, predictive modelling, information management, and decision-support initiatives.
The successful candidate will analyze large and complex datasets, develop predictive and analytical models, integrate data from multiple sources, and generate actionable insights to support business, program, regulatory, planning, and decision-making objectives.
A strong background in
geospatial and spatial data analysis, predictive analytics, machine learning, SQL, Python/R, data visualization, and analytics platforms such as Power BI, Tableau, R Shiny, or ArcGIS is essential.
Key Responsibilities
- Analyze complex structured, semi-structured, unstructured, historical, and legacy datasets to identify patterns, trends, relationships, and actionable insights.
- Develop predictive models, statistical models, machine learning solutions, and analytical frameworks to support business strategies and decision-making.
- Conduct research and initiate innovative information studies and statistical analysis initiatives.
- Identify business problems that can be addressed through data analytics and translate business requirements into analytical solutions.
- Identify, collect, integrate, and analyze relevant data sources and large datasets.
- Perform data mining, statistical analysis, pattern recognition, and predictive analytics.
- Analyze data quality issues, including duplicate records, inconsistencies, missing values, and invalid data.
- Support data migration, digitization, modernization, records conversion, and information management initiatives.
- Integrate and interpret data from multiple platforms and repositories.
- Analyze and integrate both spatial and non-spatial datasets to support planning, compliance, reporting, and evidence-based decision-making.
- Develop and apply geospatial analysis techniques and spatial data management practices.
- Build dashboards, reports, visualizations, maps, and analytical products for technical and non-technical stakeholders.
- Develop data-driven solutions to improve business performance and organizational decision-making.
- Collaborate with business stakeholders, information management specialists, GIS specialists, business analysts, project teams, and technical resources.
- Prepare technical documentation, data dictionaries, source-to-target mapping documents, data flow diagrams, and business reports.
- Apply emerging technologies, innovative analytical approaches, and industry best practices to complex business challenges.
- Support and contribute to data governance, metadata management, master data management, and data lineage initiatives.
Requirements
Mandatory Technical Skills and Experience
Data Analytics & Data Management
- Strong knowledge of information management and data management principles.
- Experience with database architecture, database management systems, relational databases, and data integration.
- Knowledge of data governance, metadata management, master data management, and data lineage.
- Experience with ETL processes, data warehousing, and data integration methodologies.
- Experience managing and analyzing structured, semi-structured, unstructured, historical, and legacy datasets.
- Knowledge of data modernization, digitization methodologies, records conversion, and data quality improvement practices.
Advanced Analytics & Data Science
- Strong proficiency in statistical analysis, mathematics, data mining, and predictive analytics.
- Extensive experience with artificial intelligence and machine learning techniques.
- Experience developing predictive models and analytical frameworks.
- Strong understanding of research methodologies and data modelling techniques.
- Extensive experience in pattern recognition and identifying trends and relationships within complex datasets.
SQL & Programming
- Strong proficiency in Structured Query Language (SQL) for accessing, extracting, transforming, and analyzing data across multiple platforms and repositories.
- Strong hands-on experience with Python and/or R for data analysis, modelling, automation, and data transformation.
- Experience working with large and complex datasets.
- Experience using code version control systems such as Git.
Visualization & Analytics Tools
Candidates must demonstrate proficiency with analytics and visualization platforms such as:
- Power BI
- Tableau
- R Shiny
- ArcGIS
- Or equivalent reporting, visualization, and analytical platforms
Geospatial & Spatial Data – Mandatory
- Demonstrated knowledge of geospatial analysis and spatial data management.
- Experience analyzing relational databases and spatial datasets.
- Ability to analyze, integrate, and interpret both spatial and non-spatial datasets.
- Experience applying geospatial analysis techniques to support planning, compliance, reporting, and decision-making.
- Ability to communicate geospatial findings through maps, dashboards, reports, presentations, and visualization tools.
Research, Analytical & Problem-Solving Skills
- Ability to assess complex datasets and identify data quality issues.
- Experience documenting business data requirements and translating them into analytical solutions.
- Ability to identify trends, patterns, relationships, and insights within large datasets.
- Experience integrating data from multiple sources and repositories.
- Ability to develop and apply predictive models, business intelligence solutions, and geospatial analytical techniques.
- Strong ability to provide recommendations supporting evidence-based decision-making.
- Ability to apply innovative analytical approaches and emerging technologies to solve complex business problems.
Communication & Collaboration Skills
- Excellent verbal and written communication skills.
- Ability to communicate complex analytical findings to both technical and non-technical audiences.
- Experience preparing technical documentation and analytical reports.
- Experience creating data dictionaries, source-to-target mapping documents, and data flow diagrams.
- Ability to present analytical findings through dashboards, reports, maps, and presentations.
- Strong stakeholder management, interpersonal, and negotiation skills.
- Ability to facilitate discussions and present recommendations to support informed decision-making.
- Proven ability to work effectively within multidisciplinary teams and complex project environments.
- Strong project management and organizational skills with a proven ability to meet deadlines.
Information Management & Standards
- Knowledge of information management standards and data governance frameworks.
- Awareness of accessibility requirements and applicable GO-ITS standards.
- Understanding of emerging I&IT trends and technologies.
Preferred Qualifications
- Advanced degree in Statistics, Data Science, Social Sciences, Computer Science, Analytics, or a related discipline.
- Data science or analytics certifications such as:
- IBM Data Science Professional Certificate
- Google Data Engineer Certification
- Other relevant data science, analytics, AI, or machine learning certifications
Key Mandatory Requirements – Candidate Screening Checklist
Candidates must clearly demonstrate experience in the following areas:
- Data analytics and relational databases
- Geospatial analysis
- Spatial data management
- Data visualization and analytical frameworks
- Power BI, Tableau, R Shiny, ArcGIS, or equivalent analytics platforms
- Analysis, integration, and interpretation of both spatial and non-spatial datasets
- Predictive modelling and analytical frameworks
- Business intelligence solutions
- Geospatial analysis techniques
- SQL
- Python and/or R
- Statistical analysis and data mining
- Machine learning and AI
- Large and complex datasets
- Data integration and ETL
- Data quality assessment
- Data governance and information management
- Excellent communication and stakeholder collaboration skills
