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.

Solid 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⁢ 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

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

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📌 Data Scientist – Senior (Ontario)
🏢 Joblinxsapp
📍 Ontario