RQ00242 - Data Science Developer - Senior

Flexstaf IT; Toronto; Hybrid; CAD 90,000 - 150,000; Full time

Job summary

Flexstaf IT in Toronto seeks a Senior Data Analytical Specialist/Scientist to develop advanced analytics, predictive models, and AI-driven insights addressing priority business opportunities. You will apply statistical, ML, and analytical techniques to enterprise data, supporting data maturity assessments, model validation, and business-value analysis.

Collaborating with Data Engineers, Product Managers, and tech teams, you will design prototypes, define KPIs, and translate complex findings into

Qualifications

• Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering or related field.
• Significant experience in data science, analytics, predictive modelling or ML.

Responsibilities

• Design and develop advanced analytics, predictive models, and ML solutions for priority business use cases.
• Conduct exploratory data analysis to identify patterns, trends, and opportunities for improved decision-making.
• Translate business problems into analytical approaches, defining hypotheses, methodologies, and success measures.
• Assess data quality and readiness for AI and analytics use cases.
• Collaborate with data engineers and product teams to operationalize successful models and analytics solutions.

Skills

Python

SQL

Statistics

Machine Learning

Predictive Modelling

Education

Bachelor's degree in Data Science

Tools

Power BI

Databricks

Azure OpenAI

Azure Foundry

Azure ML Studio

VSCode

Git

Jira

Job description

Supplier Comments

MSP Notes

Shortlist Date: Nov 9, 2026 10:00am

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.

Location: Hybrid - 3 days a week onsite

Public Sector Experience: preferred but not required

# of submissions/supplier: 1

Job Title

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.