Senior Data Analytical Specialist / Scientist

Position Overview

The Government Services Integration Cluster (GSIC), within the Ministry of Public and Business Service Delivery and Procurement, is seeking an experienced Senior Data Analytical Specialist / Scientist to lead the development and delivery of advanced analytics, data science solutions, statistical models, machine learning algorithms, and business intelligence capabilities.

The successful candidate will work closely with business stakeholders, data architects, ETL developers, and technical teams to transform complex, high-volume, structured and unstructured datasets into reliable, actionable insights. The role requires strong expertise in SQL, data manipulation, cloud environments, big data frameworks, predictive modelling, deep learning, and modern .NET and Azure-based development technologies.

The ideal candidate will combine advanced analytical and programming capabilities with practical experience supporting large government applications, cloud services, DevOps, CI/CD pipelines, and Agile delivery methodologies.

Key Responsibilities

• Lead the development and delivery of functional and ministry-specific analytics to support evidence-based decision-making and generate actionable insights.
• Assess existing data analytics, reporting capabilities, and business processes; gather future-state requirements and identify opportunities for improvement.
• Own the end-to-end execution of analytics initiatives, including data sourcing, extraction, transformation, modelling, analysis, reporting, and dataset delivery.
• Develop, train, test, validate, and deploy predictive algorithms, classification models, statistical models, machine learning solutions, and deep learning frameworks.
• Apply appropriate analytical techniques and algorithms to model business scenarios, identify patterns, and derive meaningful and reliable inferences.
• Source, clean, transform, structure, and manipulate complex datasets from multiple channels, including messy, high-volume, structured, and unstructured data sources.
• Develop complex SQL queries and support the querying, management, and analysis of large relational databases.
• Leverage cloud environments, including Microsoft Azure and AWS, and apply cloud-based services to support data processing, analytics, and solution delivery.
• Work with big data frameworks to process and analyse large and complex datasets efficiently.
• Contribute to the development and integration of custom Web APIs and applications using ASP.NET, .NET Core, Entity Framework, and Azure SQL.
• Support DevOps practices, CI/CD pipelines, software integration, testing, deployment, and ongoing improvement of analytics solutions.
• Apply cloud service models, including Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), to support appropriate technical solutions.
• Collaborate with data architects, ETL developers, functional experts, application development teams, and other stakeholders to design effective business intelligence solutions.
• Design data capture, processing, transformation, and modelling approaches that produce accurate, understandable, consistent, and unbiased analytical outputs.
• Develop meaningful data visualizations, reports, dashboards, and user-friendly interfaces to communicate complex quantitative findings.
• Translate technical and analytical results into clear recommendations, summaries, and proactive insights for technical and non-technical audiences.
• Facilitate stakeholder discussions, manage client expectations, support decision-making, and provide guidance on translating analytical findings into business actions.
• Participate in requirements gathering, solution documentation, technical reviews, development, testing, assessments, and end-user training.
• Work within Agile delivery environments, including the use of Kanban boards, task boards, and collaborative planning practices.
• Maintain awareness of emerging business intelligence, cloud computing, machine learning, data science, and analytical technologies.

Mandatory Technical Skills and Experience

1. Technical Skills – 40%

Candidates must demonstrate the following

• Coding, data manipulation, and SQL: Strong proficiency in programming, data manipulation, and SQL for querying and managing large relational databases.
• Data preparation and transformation: Hands-on experience sourcing, cleaning, transforming, and structuring messy or unstructured datasets from multiple channels.
• Cloud environments: More than five years of experience working with cloud environments such as Microsoft Azure and/or AWS.
• Big data frameworks: More than five years of experience with big data frameworks and technologies for processing and analysing large datasets.
• Predictive analytics and machine learning: Practical experience training, testing, validating, and deploying predictive algorithms and classification models.
• Deep learning: Experience working with deep learning frameworks such as TensorFlow or PyTorch.
• Custom API and .NET development: Experience with custom Web API development, ASP.NET, .NET Core, and Entity Framework.
• Azure SQL: Experience with Azure SQL and its application in data-driven solutions.
• DevOps and CI/CD: Experience with DevOps practices and CI/CD pipelines to support integration, testing, deployment, and delivery.
• Cloud service models: Proficiency in SaaS, PaaS, and IaaS cloud service models.

2. Relevant Experience – 40%

Candidates must demonstrate

• Experience supporting or working with large-scale government applications.
• Experience with cloud platforms, particularly Microsoft Azure.
• Experience delivering technical solutions involving custom Web APIs, ASP.NET, .NET Core, Entity Framework, Azure SQL, DevOps, and CI/CD pipelines.
• Ability to apply cloud service models—SaaS, PaaS, and IaaS—to enterprise application and analytics environments.
• Experience working in Agile delivery environments, including Kanban and task boards.
• Ability to collaborate with cross-functional teams, business stakeholders, architects, developers, and data specialists to deliver enterprise-grade solutions.

3. Communication Skills – 20%

Candidates must demonstrate

• Strong written and verbal communication skills.
• Ability to prepare clear and comprehensive documentation, including technical documents, reports, reviews, and assessments.
• Ability to present ideas, recommendations, and suggestions clearly and effectively in a user-friendly manner.
• Ability to communicate technical designs, analytical methods, development approaches, and solution outcomes to both technical and non-technical audiences.
• Strong interpersonal, consulting, relationship management, and stakeholder engagement skills.
• Ability to elicit requirements, evaluate solution options, provide effective guidance, and maintain a high standard of customer service for internal and external clients.
• Ability to facilitate decision-making, manage expectations, and explain complex analytical findings in an understandable and actionable format.

Additional General and Analytical Competencies

The following capabilities are also relevant to the position:

• Strong analytical, investigative, logical reasoning, problem-solving, and decision-making skills.
• Advanced understanding of mathematics, statistics, statistical analysis, and modelling.
• Experience with data mining, machine learning algorithms, natural language processing, and related analytical disciplines.
• Understanding of data management, database architecture, financial and business analysis, and information visualization.
• Experience developing data extraction, transformation, and loading (ETL) functionality for large relational and multidimensional data stores.
• Ability to design high-quality interfaces that present complex information meaningfully to end users.
• Knowledge of business intelligence trends, analytical software, and emerging data science technologies.
• Experience with tools such as R, PowerPivot, MATLAB, SPSS, SAS, Microsoft Excel, Microsoft Access, and VBA is an asset.

Ideal Candidate Profile

The ideal candidate is a senior data science and analytics professional who combines advanced data analysis and machine learning capabilities with hands-on cloud and application development experience. The candidate should be comfortable working in a complex government environment, collaborating with multidisciplinary teams, and delivering secure, reliable, scalable, and user-friendly analytical solutions.

Candidates should be able to demonstrate their experience through specific projects involving SQL, cloud platforms, big data frameworks, predictive modelling, deep learning, Azure-based technologies, .NET development, and enterprise delivery practices.

Important Submission Requirements

• Mandatory onsite commitment: The candidate must be available to work onsite five days per week at 222 Jarvis Street, Toronto, Ontario.
• Mandatory technical alignment: All specified must-have skills should be clearly demonstrated in the submitted resume.
• Cloud and big data experience: Clearly state the duration of experience with Azure/AWS and big data frameworks.
• Machine learning and deep learning: Include concrete examples of training, testing, and deploying predictive algorithms, classification models, and TensorFlow/PyTorch solutions.
• Microsoft technology stack: Explicitly demonstrate experience with custom Web APIs, ASP.NET, .NET Core, Entity Framework, Azure SQL, DevOps, and CI/CD pipelines.
• Government experience: Highlight relevant experience supporting large government applications, where applicable.
• Agile delivery: Include examples of using Agile methodologies and Kanban/task boards.
• Security: The assignment specifies CRJMC security clearance.
• Submission limit: Only one candidate may be submitted for this requisition.

Submission deadline

November 3, 2026, at 12:00 PM EST.

Requirements

Mandatory Technical Skills and Experience

1. Technical Skills

Candidates must demonstrate the following

• Coding, data manipulation, and SQL: Strong proficiency in programming, data manipulation, and SQL for querying and managing large relational databases.
• Data preparation and transformation: Hands-on experience sourcing, cleaning, transforming, and structuring messy or unstructured datasets from multiple channels.
• Cloud environments: More than five years of experience working with cloud environments such as Microsoft Azure and/or AWS.
• Big data frameworks: More than five years of experience with big data frameworks and technologies for processing and analysing large datasets.
• Predictive analytics and machine learning: Practical experience training, testing, validating, and deploying predictive algorithms and classification models.
• Deep learning: Experience working with deep learning frameworks such as TensorFlow or PyTorch.
• Custom API and .NET development: Experience with custom Web API development, ASP.NET, .NET Core, and Entity Framework.
• Azure SQL: Experience with Azure SQL and its application in data-driven solutions.
• DevOps and CI/CD: Experience with DevOps practices and CI/CD pipelines to support integration, testing, deployment, and delivery.
• Cloud service models: Proficiency in SaaS, PaaS, and IaaS cloud service models.

2. Relevant Experience

Candidates must demonstrate

• Experience supporting or working with large-scale government applications.
• Experience with cloud platforms, particularly Microsoft Azure.
• Experience delivering technical solutions involving custom Web APIs, ASP.NET, .NET Core, Entity Framework, Azure SQL, DevOps, and CI/CD pipelines.
• Ability to apply cloud service models—SaaS, PaaS, and IaaS—to enterprise application and analytics environments.
• Experience working in Agile delivery environments, including Kanban and task boards.
• Ability to collaborate with cross-functional teams, business stakeholders, architects, developers, and data specialists to deliver enterprise-grade solutions.

3. Communication Skills

Candidates must demonstrate

• Strong written and verbal communication skills.
• Ability to prepare clear and comprehensive documentation, including technical documents, reports, reviews, and assessments.
• Ability to present ideas, recommendations, and suggestions clearly and effectively in a user-friendly manner.
• Ability to communicate technical designs, analytical methods, development approaches, and solution outcomes to both technical and non-technical audiences.
• Strong interpersonal, consulting, relationship management, and stakeholder engagement skills.
• Ability to elicit requirements, evaluate solution options, provide effective guidance, and maintain a high standard of customer service for internal and external clients.
• Ability to facilitate decision-making, manage expectations, and explain complex analytical findings in an understandable and actionable format.

Additional General and Analytical Competencies

The following capabilities are also relevant to the position:

• Strong analytical, investigative, logical reasoning, problem-solving, and decision-making skills.
• Advanced understanding of mathematics, statistics, statistical analysis, and modelling.
• Experience with data mining, machine learning algorithms, natural language processing, and related analytical disciplines.
• Understanding of data management, database architecture, financial and business analysis, and information visualization.
• Experience developing data extraction, transformation, and loading (ETL) functionality for large relational and multidimensional data stores.
• Ability to design high-quality interfaces that present complex information meaningfully to end users.
• Knowledge of business intelligence trends, analytical software, and emerging data science technologies.
• Experience with tools such as R, PowerPivot, MATLAB, SPSS, SAS, Microsoft Excel, Microsoft Access, and VBA is an asset.

Ideal Candidate Profile

The ideal candidate is a senior data science and analytics professional who combines advanced data analysis and machine learning capabilities with hands-on cloud and application development experience. The candidate should be comfortable working in a complex government environment, collaborating with multidisciplinary teams, and delivering secure, reliable, scalable, and user-friendly analytical solutions.

Candidates should be able to demonstrate their experience through specific projects involving SQL, cloud platforms, big data frameworks, predictive modelling, deep learning, Azure-based technologies, .NET development, and enterprise delivery practices.

Important Submission Requirements

• Mandatory onsite commitment: The candidate must be available to work onsite five days per week at 222 Jarvis Street, Toronto, Ontario.
• Mandatory technical alignment: All specified must-have skills should be clearly demonstrated in the submitted resume.
• Cloud and big data experience: Clearly state the duration of experience with Azure/AWS and big data frameworks.
• Machine learning and deep learning: Include concrete examples of training, testing, and deploying predictive algorithms, classification models, and TensorFlow/PyTorch solutions.
• Microsoft technology stack: Explicitly demonstrate experience with custom Web APIs, ASP.NET, .NET Core, Entity Framework, Azure SQL, DevOps, and CI/CD pipelines.
• Government experience: Highlight relevant experience supporting large government applications, where applicable.
• Agile delivery: Include examples of using Agile methodologies and Kanban/task boards.
• Security: The assignment specifies CRJMC security clearance.

Submission deadline

November 3, 2026, at 12:00 PM EST.