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Application & Systems Operations Delivery Lead
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- Full-time
…and collaborating with DBAs to ensure a healthy and resilient data…
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- Full-time
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Russell Tobin

Senior Data Science Developer

Toronto, ON, Canada

$60 to $70 CAD / hour · Contract

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Job details

Pay: $60 to $70 CAD / hour
Job type: Contract
Apply by: Dec 4, 2026
Posting language: English
Posted: Nov 4, 2026

Original job description

Russell Tobin & Associates is hiring on behalf of one of its esteemed clients.

Job Title: Senior Data Science Developer

Location: Toronto, ON (Hybrid – 3 days a week onsite)

Duration: 130 business days

Client: Public Sector

Pay Rate: $60 - $70/hr [CAD]

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.

Must Haves:

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 but not required

If this opportunity matches your experience and career goals, please share your most updated resume for consideration.

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More about this job

Responsibilities

Develop and validate predictive models, machine learning solutions, and prototypes, while assessing data readiness and identifying valuable analytics opportunities. Collaborate with business and technology teams to operationalize solutions, monitor outcomes, and communicate findings while applying responsible AI, privacy, and governance practices.

Requirements

Requires significant experience in data science, advanced analytics, predictive modeling, or machine learning, with deep expertise in statistics and hands-on proficiency in Python, SQL, and ML frameworks. Candidates should have experience with Azure Machine Learning and Microsoft Foundry, model development and validation using real-world data, and the ability to connect analytical work to business outcomes.

Skills

Python
SQL
Statistics
Probability
Predictive Modeling
Machine Learning
Statistical Inference
Feature Engineering
Model Validation
Azure Machine Learning
Microsoft Foundry
Databricks
Power BI
Data Analysis
Responsible AI
Stakeholder Management

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Advanced Analytics
Predictive Modeling
Machine Learning
Statistical Analysis
Python
SQL
Power BI
VSCode
Git
Jira
Azure
Azure OpenAI
Microsoft Foundry
Azure AI Foundry
Azure Machine Learning
ML Studio
Databricks
Exploratory Data Analysis
Feature Engineering
Model Evaluation
Model Validation
Experimentation
Data Quality
Responsible AI
Data Governance
Generative AI
Classification
Regression
Clustering

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