Rq00242 - Senior Data Analytical Specialist/Scientist

Client: Metrolinx – RQ00242
We are seeking a highly skilled
Senior Data Analytical Specialist/Scientist
with strong expertise in data science, advanced analytics, statistical analysis, predictive modelling, and machine learning. The ideal candidate will have hands‑on experience developing, tuning, and validating machine learning models using real‑world enterprise datasets, along with advanced proficiency in Python, SQL, and modern cloud‑based AI and analytics platforms. The successful candidate will develop advanced analytical solutions, generate AI‑driven insights, identify high‑value business opportunities, and work closely with cross‑functional teams to operationalize predictive models and deliver measurable business outcomes.
Role Snapshot
Job Title: RQ00242 – Senior Data Analytical Specialist/Scientist
Client: Metrolinx
Work Location: 277 Front Street West, Toronto, Ontario, Canada
Work Arrangement: Hybrid – 3 Days Onsite per Week
Estimated Start Date: November 23, 2026
Estimated End Date: May 23, 2027
Business Days: 130.00
Hours: 7.25 hours per day
Job Type: Contract
Public Sector Experience: Preferred but not required
Must Have
Deep expertise in statistics, probability, predictive modelling, and machine learning, including:
Classification
Regression
Clustering
Feature Engineering
Experimentation
Model Selection
Model Validation
Bias/Variance
Overfitting
Statistical Inference
Advanced hands‑on proficiency in Python, SQL, and ML frameworks, with demonstrated experience building, tuning, and validating models using real‑world datasets.
Strong experience with the following technology stack:
Python
SQL
Power BI
VS Code
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.
DescriptionThe 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.
Additional InformationWork Arrangement
This is a Hybrid position.
The selected candidate is required to work onsite 3 days per week at the client's location: 277 Front Street West, Toronto, Ontario, Canada.
Public Sector Experience
Public Sector experience is preferred but not required.
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