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Added 16 mins ago
DR
Technology Specialist, Networking
Durham Region (The Regional Municipality of Durham)
Whitby, ON
- Temporary
…continuous improvement of network resources. The incumbent will support the design, implementation and operation of the Region's Local Area Network, Wide Area Network and enterprise…
Added 1 hour ago
SM
RQ00242 – Senior Data Analytical Specialist/Scientist
S M Software Solutions Inc
Toronto, ON
- Full-time
We are seeking a highly skilled Senior Data Analytical Specialist/Scientist with strong expertise in data science, advanced analytics, statistical analysis, predictive modelling, and…
Added 1 hour ago
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- Full-time
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S M Software Solutions Inc

RQ00242 – Senior Data Analytical Specialist/Scientist

Toronto, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Dec 5, 2026
Posting language: English
Posted: Nov 5, 2026

Original job description

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.

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.

Additional Information

Work 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.

How to Apply

If you are interested and your profile matches the requirements, kindly submit the following mandatory documents to hrsmss@smsoftconsulting.com by Monday, November 9, 2026, at 8:00 AM EST.

Mandatory Documents

Updated Resume in Word format (Mandatory)
Skills Matrix and References (Mandatory)
Expected Hourly Rate (Mandatory)
Visa Status (Mandatory)
LinkedIn ID (Mandatory)

Without the mandatory documents, we cannot proceed with your submission.

WhatsApp Group

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WhatsApp Group Link: Link

Additional Information

Email is the best way to reach us.

You have received this message either as a result of contacting our company to express interest in employment or as a result of posting your resume in a location that can be accessed by recruiters or HR specialists, which suggests an interest in being contacted about employment opportunities.

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More about this job

Responsibilities

Develop and validate advanced analytics and machine learning solutions, including predictive models and prototypes, to address priority business opportunities. Collaborate with stakeholders and technical teams to operationalize solutions, assess business value, monitor outcomes, and communicate findings while applying responsible AI, privacy, and governance practices.

Requirements

Requires significant experience in data science, advanced analytics, predictive modeling, machine learning, or statistical analysis, with strong proficiency in Python, SQL, and model development and validation using enterprise data. A degree in a quantitative field or equivalent experience is required, along with cloud analytics experience, business acumen, and strong communication and stakeholder-management skills.

Skills

Data Science
Advanced Analytics
Statistical Analysis
Predictive Modeling
Machine Learning
Python
SQL
Azure Machine Learning
Microsoft Foundry
Databricks
Power BI
Feature Engineering
Model Validation
Exploratory Data Analysis
Responsible AI
Stakeholder Management

Visa sponsorship

Not detected in the job text

Keywords

Python
SQL
Power BI
Visual Studio Code
Git
Jira
Azure
Azure OpenAI
Microsoft Foundry
Azure Machine Learning
Databricks
Machine Learning
Predictive Modeling
Statistical Inference
Classification
Regression
Clustering
Feature Engineering
Experimentation
Model Selection
Model Validation
Exploratory Data Analysis
Data Quality
Generative AI
Responsible AI
Data Governance
Model Risk
Data Maturity Assessment
Business Value Analysis
Enterprise Data

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