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RQ00746 - Data Analytical Specialist/Scientist - Senior

Hybrid
Toronto, Ontario, Canada
Senior Level
Full-Time

About the role

Senior Data Analytical Specialist / Scientist

Client: Supply Ontario (Public Health Ontario – PHO) | Hybrid – Toronto, ON, Canada

We are seeking an experienced Senior Data Analytical Specialist / Scientist to support Public Health Ontario's (PHO) HealthMap initiative, a strategic analytics program focused on advancing public health intelligence through sophisticated statistical modeling, data science, and analytics.

The successful candidate will play a critical role in analyzing, validating, and operationalizing the Ontario Disease Burden Model (ODBM) within PHO's enterprise environment while contributing to the organization's Public Health Data Utility (PHDU) and cloud-based analytics platform. This position requires strong expertise in statistical modeling, reproducible analytical workflows, data engineering concepts, R/Python programming, and stakeholder collaboration within large-scale public sector environments.

Role Snapshot

Requisition ID: RQ00746

Job Title: Senior Data Analytical Specialist / Scientist

Client: Supply Ontario (Public Health Ontario)

Work Location: 661 University Ave, Suite 1701, Toronto, Ontario M5G 1M1, Canada

Work Arrangement: Hybrid (2 Days Onsite)

Contract Start Date: August 31, 2026

Contract End Date: March 1, 2027

Contract Duration: 131 Business Days

Schedule: 7.25 Hours per Day | Monday–Friday

Application Requirements

Kindly send the following documents to hrsmss@smsoftconsulting.com by Thursday, July 30, 2026, at 12:00 AM EST if this opportunity matches your experience and interests.

Mandatory Documents

Updated Resume (Word Format)

Skills Matrix and References Expected Hourly Rate Visa Status LinkedIn Profile URL

Note: Applications submitted without all mandatory documents cannot be processed.

Position Summary

HealthMap is Public Health Ontario's flagship analytics initiative, designed to transform provincial public health data into actionable intelligence, surveillance, forecasting, and decision support.

The Senior Data Analytical Specialist / Scientist will be dedicated to the HealthMap program, working closely with business and technical teams to analyze, build, validate, and operationalize the Ontario Disease Burden Model (ODBM) developed by the Dalla Lana School of Public Health (University of Toronto).

This role requires expertise in advanced statistical methodologies, reproducible analytical workflows, cloud-based analytics, and public health data while ensuring long-term sustainability through comprehensive documentation and knowledge transfer.

Key Responsibilities

Statistical Modeling & Advanced Analytics (45%)

Analyze the Ontario Disease Burden Model (ODBM) methodology and supporting datasets. Build, validate, and operationalize statistical models within PHO's enterprise environment. Evaluate model assumptions, logic, and performance. Develop reproducible analytical workflows supporting sustainable model execution. Support forecasting, scenario analysis, and evidence-based public health decision-making.

Data Engineering & Analytical Workflows (25%)

Design and implement data ingestion, transformation, and quality validation processes. Develop reproducible analytical pipelines using version-controlled code. Work with structured and unstructured datasets to support advanced analytics. Support integration with the Public Health Data Utility (PHDU) and Azure-based analytics platform. Collaborate with data engineers, architects, and ETL development teams.

Stakeholder Collaboration & Solution Delivery (20%)

Partner with business stakeholders, technical teams, data stewards, and subject matter experts. Assess business requirements and recommend analytical solutions. Communicate complex quantitative methods and analytical findings to both technical and non-technical audiences. Support governance activities and data-sharing initiatives required for model implementation.

Documentation & Knowledge Transfer (10%)

Produce comprehensive technical and methodological documentation. Deliver knowledge transfer sessions to PHO technical teams. Develop sustainable operational procedures and implementation guidelines. Support testing, end-user training, and transition activities.

Key Deliverables

Fully documented analytical methodologies and technical processes

Operational Ontario Disease Burden Model (ODBM) within PHO's environment Reproducible analytical workflows and validated statistical models Data acquisition and governance documentation Knowledge transfer materials and technical training sessions Sustainable analytical capability aligned with the Public Health Data Utility (PHDU)

Required Skills & Experience

Skill / Experience Required Advanced analytical, problem-solving, and decision-making skills Required Senior-level statistical modeling and validation experience Required Designing reproducible analytical workflows Required Data ingestion, transformation, and quality assurance processes Required Structured and unstructured data analysis Required R and/or Python programming Required SQL and query language proficiency Required Version-controlled analytical code development Required Data management and governance knowledge Required Business analysis and stakeholder consulting Required Information visualization concepts Required Strong written and verbal communication skills Required Knowledge transfer and technical documentation Required

Preferred Qualifications

Experience with R and Power BI

Public health or population health analytics experience Chronic disease, burden-of-disease, or microsimulation modeling experience Experience implementing academic or research models in production environments Azure cloud analytics experience Databricks platform experience Knowledge of the Accessibility for Ontarians with Disabilities Act (AODA)

Expected Professional Expertise

The Successful Consultant Will Demonstrate The Ability To

Apply advanced statistical and analytical concepts with minimal supervision. Lead complex analytical initiatives across multidisciplinary teams. Mentor technical staff and provide subject matter expertise. Deliver enterprise-level analytical solutions supporting executive decision-making. Translate complex analytical findings into actionable business recommendations. Provide strategic advisory support on data science and advanced analytics initiatives.

Preferred Candidate Profile

We are seeking professionals with expertise in

Statistical analysis and predictive modeling

Advanced data analytics and data science R and Python programming Reproducible analytical workflows Data governance and information management Public health or healthcare analytics Azure cloud analytics environments Knowledge transfer and stakeholder engagement

Additional Information

Public sector experience is required.

Work Model: Hybrid (2 Days Onsite)

Location: Toronto, Ontario, Canada Public Sector Experience: Required

How To Apply

Please submit the following documents to hrsmss@smsoftconsulting.com by Thursday, July 30, 2026, at 12:00 AM EST.

Mandatory Submission Documents

Updated Resume (Word Format)

Skills Matrix and References Expected Hourly Rate Visa Status LinkedIn Profile URL

Applications missing any of the required documents cannot be considered.

If this opportunity is not the right fit for you, we encourage you to share it with qualified professionals experienced in Data Science, Statistical Modeling, R, Python, Public Health Analytics, Predictive Modeling, Azure Analytics, Data Governance, and Advanced Analytical Workflows.

About S M Software Solutions Inc

IT Services and IT Consulting

SMSS Inc. is the best solution company specialized in providing Information Technology and Management Consulting. We provide value for money to our clients by delivering the best quality technical services and solutions at reasonable rates. We also provide the best working environment for our staff and consultants. It is a growing IT services provider having wide array of solutions from Business Strategy Analysis to implementation and execution of Information Technology as well as management aspects of a business entity.

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