Data Scientist

Role - Data Science Developer - Senior

Duration - Contract for 130 Days

Location: 277 Front St W, Toronto, ON(Hybrid)

Ministry: Government of Canada

Job Overview

The Senior Data Analytics Specialist / Data Scientist will develop advanced analytics, predictive models, and AI-driven solutions to address key business challenges and opportunities. The role involves applying statistical analysis, machine learning, and predictive modelling techniques to enterprise data to generate actionable insights and support data-driven decision-making.

The successful candidate will contribute to enterprise data maturity assessments, model validation, business-value analysis, and the identification of high-value AI and advanced analytics opportunities. This role will work closely with Data Engineers, Data Architects, Product Managers, and business stakeholders to develop and operationalize scalable analytical solutions.

Key Responsibilities

• Design, develop, and implement advanced analytics, predictive models, and machine learning solutions for priority business use cases.
• Perform exploratory data analysis (EDA) to identify patterns, trends, relationships, and business opportunities.
• Translate business requirements into analytical approaches, hypotheses, modelling methodologies, and measurable success criteria.
• Assess data quality, availability, and readiness for AI and advanced analytics initiatives.
• Support enterprise data maturity and analytics capability assessments and recommend improvements.
• Develop, validate, tune, and optimize machine learning and predictive models using appropriate statistical techniques.
• Evaluate model performance, assumptions, limitations, bias, and reliability.
• Collaborate with business stakeholders to identify high-value AI and analytics opportunities and assess feasibility and business value.
• Develop prototypes and proofs of concept (POCs) to evaluate analytical approaches before enterprise implementation.
• Work with Data Engineers, Data Architects, Product Managers, and technology teams to operationalize analytical and machine learning solutions.
• Define and monitor analytical KPIs to measure business outcomes and solution effectiveness.
• Present complex analytical findings and recommendations to technical teams, business stakeholders, and executive leadership.
• Ensure Responsible AI, data privacy, governance, and model risk considerations are incorporated throughout the analytics lifecycle.

Qualifications and Experience

• Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative discipline, or equivalent experience.
• Significant experience in Data Science, Advanced Analytics, Predictive Modelling, Machine Learning, or Statistical Analysis.
• Strong hands-on proficiency in Python and SQL, including statistical analysis and machine learning techniques.
• Proven experience developing, tuning, and validating predictive and machine learning models using real-world enterprise datasets.
• Strong understanding of statistical modelling, probability, experimentation, feature engineering, model evaluation, and data quality.
• Experience working with modern cloud-based data science and analytics platforms.
• Knowledge of Generative AI, Azure AI services, and emerging AI technologies is an asset.
• Strong business acumen with the ability to translate analytical insights into measurable business outcomes.
• Excellent analytical, problem-solving, communication, and stakeholder-management skills.

Must-Have Skills

• Deep expertise in statistics, probability, predictive modelling, and machine learning, including classification, regression, clustering, feature engineering, experimentation, model selection, model validation, bias-variance trade-offs, overfitting, and statistical inference.
• Advanced hands-on proficiency in Python, SQL, and machine learning frameworks, with demonstrated experience building, tuning, and validating models using real-world datasets.
• Strong hands-on experience with Azure Machine Learning and Microsoft Foundry (Azure AI Foundry), including end-to-end machine learning pipelines covering experimentation, model training, evaluation, and operationalization.

Technical Skills and Tools

• Programming & Analytics: Python, SQL
• Machine Learning: Predictive Modelling, Classification, Regression, Clustering, Statistical Analysis, Feature Engineering
• Microsoft Azure AI: Azure OpenAI, Microsoft Foundry (Azure AI Foundry), Azure Machine Learning Studio
• Data & Analytics Platforms: Azure Databricks, Power BI
• Development & Collaboration Tools: Visual Studio Code (VS Code), Git, Jira

Employment Practices:

VLink is an equal opportunity employer committed to fostering an inclusive environment where diversity is celebrated. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. Employment is contingent upon successful completion of a background check.

This job application process may use AI-powered tools to assist in screening and evaluating applications based on objective, job-related qualifications. AI is used solely to support the recruitment process and all final hiring decisions are made exclusively by our human recruitment team.

Applicant information will be handled in accordance with VLink's privacy policy.