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We are seeking an experienced Senior Data Analytical Specialist/Scientist to lead the development and delivery of advanced analytics, machine learning solutions, and data pipelines that drive evidence-based decision-making. In this role, you will be responsible for sourcing, cleaning, and transforming complex, unstructured datasets from diverse ...
channels, and building robust statistical models and deep learning algorithms. Combining data science with cloud architecture and software engineering practices, you will develop custom APIs, deploy predictive models into production environments, and collaborate closely with cross-functional stakeholders to translate complex quantitative findings into clear, actionable business insights. Location: Toronto, ON (Fully Onsite - 5 days/week required) Duration: 11-month contract. Advantages End-to-End Analytics Scope: Lead full-lifecycle data science from data engineering to predictive model deployment. Modern Hybrid Tech Stack: Hands-on work combining machine learning frameworks with .NET Core and Azure cloud architectures. High-Impact Insights: Translate complex analytical findings directly into strategic decision-making. Collaborative Onsite Environment: Partner closely with data architects, developers, and leadership in a dedicated Toronto workspace. Responsibilities Lead the end-to-end design, development, and delivery of advanced analytics initiatives, statistical models, and reporting datasets. Source, clean, transform, and structure complex, high-volume datasets from structured and unstructured sources across multiple channels. Train, test, evaluate, and deploy predictive models, classification algorithms, and deep learning solutions using frameworks such as TensorFlow or PyTorch. Query, manipulate, and optimize large relational and multi-dimensional databases using advanced SQL. Build, deploy, and maintain custom Web APIs, backend data-access components, and cloud services using ASP.NET, .NET Core, Entity Framework, and Azure SQL. Implement and support automated CI/CD pipelines, containerization, and deployment workflows within modern cloud environments (Azure and AWS). Work with big data frameworks and distributed processing platforms to support scalable data extraction, transformation, and ingestion. Translate complex quantitative analysis, statistical inferences, and model predictions into clear visual dashboards, summaries, and executive presentations. Collaborate closely with data architects, ETL developers, product owners, and business leaders to identify analytical requirements and deliver tailored solutions. Participate in Agile delivery processes, tracking progress and managing backlogs using Kanban and task boards. Qualifications Data Manipulation & Advanced SQL: Demonstrated proficiency in coding and data manipulation, alongside advanced SQL for querying and managing large-scale relational databases (Strictly Required). Data Sourcing & Transformation: Proven ability to source, clean, transform, and structure messy or unstructured datasets from multiple channels (Strictly Required). Cloud Environments: 5+ years of hands-on experience working within enterprise cloud environments (Azure, AWS) across SaaS, PaaS, and IaaS models (Strictly Required). Big Data Frameworks: 5+ years of practical experience working with big data architectures and distributed data frameworks (Strictly Required). Machine Learning & Deep Learning: Demonstrated experience training, testing, and deploying predictive algorithms, classification models, and deep learning frameworks (such as TensorFlow or PyTorch) (Strictly Required). .NET & Cloud API Engineering: Hands-on experience with custom Web API development, ASP.NET, .NET Core, Entity Framework, Azure SQL, DevOps, and CI/CD pipelines (Strictly Required). Agile Delivery: Proven experience working in Agile delivery environments, including Kanban and task-board management (Strictly Required). Communication & Visualization: Strong verbal and written communication skills to prepare technical reports, document designs, and communicate quantitative findings to both technical and non-technical stakeholders (Strictly Required). Nice-to-Have Assets: Prior data science or analytics experience supporting large-scale enterprise or public sector systems. Experience with additional analytical software and programming languages (e.g., Python, R, SAS). Experience designing intuitive business intelligence visualizations and interactive dashboards. Summary If you're interested in the "Senior Data Analytical Specialist/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!
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We are seeking an experienced Senior Data Analytical Specialist/Scientist to lead the development and delivery of advanced analytics, machine learning solutions, and data pipelines that drive evidence-based decision-making. In this role, you will be responsible for sourcing, cleaning, and transforming complex, unstructured datasets from diverse channels, and building robust statistical models and deep learning algorithms. Combining data science with cloud architecture and software engineering practices, you will develop custom APIs, deploy predictive models into production environments, and collaborate closely with cross-functional stakeholders to translate complex quantitative findings into clear, actionable business insights. Location: Toronto, ON (Fully Onsite - 5 days/week required) Duration: 11-month contract. Advantages End-to-End Analytics Scope: Lead full-lifecycle data science from data engineering to predictive model deployment. Modern Hybrid Tech Stack: Hands-on work combining machine learning frameworks with .NET Core and Azure cloud architectures. High-Impact Insights: Translate complex analytical findings directly into strategic decision-making. ...
Collaborative Onsite Environment: Partner closely with data architects, developers, and leadership in a dedicated Toronto workspace. Responsibilities Lead the end-to-end design, development, and delivery of advanced analytics initiatives, statistical models, and reporting datasets. Source, clean, transform, and structure complex, high-volume datasets from structured and unstructured sources across multiple channels. Train, test, evaluate, and deploy predictive models, classification algorithms, and deep learning solutions using frameworks such as TensorFlow or PyTorch. Query, manipulate, and optimize large relational and multi-dimensional databases using advanced SQL. Build, deploy, and maintain custom Web APIs, backend data-access components, and cloud services using ASP.NET, .NET Core, Entity Framework, and Azure SQL. Implement and support automated CI/CD pipelines, containerization, and deployment workflows within modern cloud environments (Azure and AWS). Work with big data frameworks and distributed processing platforms to support scalable data extraction, transformation, and ingestion. Translate complex quantitative analysis, statistical inferences, and model predictions into clear visual dashboards, summaries, and executive presentations. Collaborate closely with data architects, ETL developers, product owners, and business leaders to identify analytical requirements and deliver tailored solutions. Participate in Agile delivery processes, tracking progress and managing backlogs using Kanban and task boards. Qualifications Data Manipulation & Advanced SQL: Demonstrated proficiency in coding and data manipulation, alongside advanced SQL for querying and managing large-scale relational databases (Strictly Required). Data Sourcing & Transformation: Proven ability to source, clean, transform, and structure messy or unstructured datasets from multiple channels (Strictly Required). Cloud Environments: 5+ years of hands-on experience working within enterprise cloud environments (Azure, AWS) across SaaS, PaaS, and IaaS models (Strictly Required). Big Data Frameworks: 5+ years of practical experience working with big data architectures and distributed data frameworks (Strictly Required). Machine Learning & Deep Learning: Demonstrated experience training, testing, and deploying predictive algorithms, classification models, and deep learning frameworks (such as TensorFlow or PyTorch) (Strictly Required). .NET & Cloud API Engineering: Hands-on experience with custom Web API development, ASP.NET, .NET Core, Entity Framework, Azure SQL, DevOps, and CI/CD pipelines (Strictly Required). Agile Delivery: Proven experience working in Agile delivery environments, including Kanban and task-board management (Strictly Required). Communication & Visualization: Strong verbal and written communication skills to prepare technical reports, document designs, and communicate quantitative findings to both technical and non-technical stakeholders (Strictly Required). Nice-to-Have Assets: Prior data science or analytics experience supporting large-scale enterprise or public sector systems. Experience with additional analytical software and programming languages (e.g., Python, R, SAS). Experience designing intuitive business intelligence visualizations and interactive dashboards. Summary If you're interested in the "Senior Data Analytical Specialist/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!
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