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 contemporary 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.

📌 Data Science Developer - Senior (Winnipeg)
🏢 FlexStaf IT
📍 Winnipeg