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.
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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.
