Senior Data Science Developer

Toronto, ON
Hybrid
Posted Nov 5, 2026
1 position

Applications are currently unavailable for this posting.

Employment type: Contract
Experience level: Senior · 5+ years
Minimum education: Bachelor’s degree
Posting language: English
Working hours: 40 hours per week
Office presence: 3 days per week
Seniority: Mid-Senior level
Application method: Apply on LinkedIn (LinkedIn sign-in required)

Job summary

Develop advanced analytics, predictive models, and machine learning solutions, including prototypes and proofs of concept, to address business priorities. Assess data readiness, validate models, identify valuable AI opportunities, operationalize successful solutions with cross-functional teams, and communicate findings and outcomes to stakeholders.

Job details

Position: Senior Data Science Developer Requisition Number: RQ00242 Type: Contract Duration: 6 months Location: Toronto Work Schedule: Hybrid Work Model: 3 days onsite / 2 days remote MANDATORY SKILLS Deep expertise in statistics, probability, predictive modelling and machine learning, including classification, regression, clustering, feature engineering, experimentation, model selection, validation, bias/variance, overfitting and statistical inference. Advanced hands-on proficiency in Python, SQL and ML frameworks, with demonstrated experience building, tuning and validating models using real-world datasets. Tech stack: Python, SQL, Power BI, VSCode, Git, Jira, Azure (OpenAI, Foundry and ML Studio), Databricks. Strong hands-on experience with Azure Machine Learning and Microsoft Foundry/Azure AI Foundry, including end-to-end ML pipelines covering experimentation, training, evaluation and operationalization. Public Sector Experience: preferred SENIOR DATA ANALYTICAL SPECIALIST/SCIENTIST DESCRIPTION The Senior Data Analytical Specialist/Scientist will develop advanced analytics, predictive models, and AI-driven insights to address priority business opportunities. The role will apply statistical, machine learning, and analytical techniques to enterprise data, while supporting data maturity assessments, model validation, business-value analysis, and the identification of high-value AI and analytics opportunities. KEY RESPONSIBILITIES Design and develop advanced analytics, predictive models, and machine learning solutions for priority business use cases. Conduct exploratory data analysis to identify patterns, trends, relationships, and opportunities for improved decision-making. Translate business problems into appropriate analytical and modelling approaches, defining hypotheses, methodologies, and success measures. Assess the quality, availability, and readiness of data required for AI and advanced analytics use cases. Support enterprise data maturity and analytics capability assessments and identify opportunities for improvement. Validate model performance using appropriate statistical and machine learning techniques and communicate model assumptions, limitations, and results. Partner with business stakeholders to identify high-value AI and analytics opportunities and assess potential business value and feasibility. Develop prototypes and proofs of concept to test analytical approaches before broader implementation. Work closely with Data Engineers, Data Architects, Product Managers, and technology teams to operationalize successful models and analytical solutions. Define and monitor analytical KPIs and support evaluation of whether delivered solutions achieve intended business outcomes. Communicate complex analytical findings and recommendations in clear, actionable terms for both technical and executive audiences. Apply appropriate Responsible AI, privacy, data governance, and model risk considerations throughout the analytics lifecycle. QUALIFICATIONS & EXPERIENCE Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field, or equivalent experience. Significant experience in data science, advanced analytics, predictive modelling, machine learning, or statistical analysis. Strong proficiency in Python, SQL, statistical analysis, and machine learning techniques. Experience developing and validating predictive and machine learning models using real-world enterprise data. Knowledge of model evaluation, experimentation, feature engineering, data quality, and analytical methodology. Experience working with modern cloud-based data and analytics environments. Understanding of Generative AI and emerging AI techniques would be an asset. Strong business acumen with the ability to connect analytical findings to measurable business outcomes. Strong communication, problem-solving, and stakeholder-management skills. REQUIRED Deep expertise in statistics, probability, predictive modelling and machine learning Advanced hands-on proficiency in Python, SQL and ML frameworks Strong hands-on experience with Azure Machine Learning and Microsoft Foundry/Azure AI Foundry Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field Significant experience in data science, advanced analytics, predictive modelling, machine learning, or statistical analysis Strong proficiency in Python, SQL PREFERRED Public Sector Experience Understanding of Generative AI and emerging AI techniques

What you’ll do

Requirements

Requires a quantitative degree or equivalent experience, significant experience in data science or advanced analytics, and strong expertise in statistics, predictive modeling, Python, SQL, and machine learning. Hands-on experience with Azure Machine Learning and Microsoft Foundry/Azure AI Foundry is required; public sector experience and knowledge of generative AI are preferred.