Data Specialist, Assessment

Esri Canada has an exceptional opportunity for a Data Specialist to join our Assessment department.

Reporting to the Director, Software Development Assessment, this role is responsible for designing, building, and maintaining reliable, scalable data pipelines and data infrastructure that enable advanced analytics, modeling, and data‑driven product capabilities. The role is focused on data ingestion, transformation, integration, performance optimization, and modeling.

Working closely with software developers, product managers, and business stakeholders, this role ensures high‑quality, well‑governed data is available for analysis and supports the development, validation, and operationalization of analytical and predictive models within an enterprise software environment.

This role is fully remote within Canada.

About us:

Esri Canada provides geographic information system (GIS) solutions that empower people in business, government and education to make informed and timely decisions by leveraging the power of mapping and spatial analytics.

If you are passionate about making an impact in an organization that’s committed to creating a sustainable future, consider joining our team!

A day in the life of a Data Specialist at Esri Canada:

• Design, develop, test, and maintain scalable, reliable data pipelines and data integration processes to support analytics, modeling, and product features.
• Build and optimize data models, data stores, and transformation workflows to ensure data performance, accuracy, and maintainability.
• Collect, ingest, clean, and integrate large volumes of structured and unstructured data from multiple internal and external sources, ensuring data quality, integrity, and analytical readiness.
• Collaborate with software developers and platform teams to integrate data pipelines and analytics capabilities into production systems and enterprise software solutions.
• Monitor, troubleshoot, and improve data pipeline performance, reliability, and scalability, contributing to operational stability and continuous improvement.
• Develop, evaluate, and refine descriptive, predictive, and diagnostic models using statistical and machine learning techniques such as regression, classification, clustering, and time series analysis.
• Translate analytical and modeling outputs into clear, actionable insights through data visualization, dashboards, reports, and presentations tailored to technical and non-technical stakeholders.
• Support the operationalization of analytical and predictive models, including deployment, monitoring, and ongoing maintenance in production environments.
• Contribute to continuous improvement initiatives by researching, evaluating, and applying emerging data engineering, analytics, and data science tools, technologies, and best practices.

General Responsibilities:

• Participate collaboratively in the company Employee Development Program.
• Communicate effectively with internal and external personnel at all levels representing the company in a professional manner at all times.
• Actively participate in company, staff or individual one-on-one meetings on an ongoing basis for the purposes of effective teamwork, enhanced communication and progressive co-operation strategies within the company as well as other departments across the company.
• Continually contribute to the profitability of the company and ongoing business operations by initiating, recommending and implementing continuous improvement strategies and initiatives.
• Conduct any general duties, specific job projects and responsibilities as assigned or required by the Director or Esri Canada management in a timely and professional manner.

Minimum Education Requirement:

• University degree in data science, computer science, statistics, mathematics, engineering, or a related quantitative discipline.

Minimum Experience and Training Requirement:

• 3+ years of experience in data analysis, data science, or applied analytics roles within a technology, consulting, or data driven business environment.
• Demonstrated experience developing and validating statistical and machine learning models using programming languages such as Python or R, and querying data using SQL.
• Experience working with large datasets and applying data preparation, feature engineering, model evaluation, and performance monitoring techniques.
• Experience creating data visualizations and analytical outputs using common visualization or business intelligence tools is considered an asset.

Additional Requirements:

• Strong analytical and problem‑solving skills, with the ability to design, troubleshoot, and optimize data pipelines, data models, and analytical workflows, as well as interpret data to identify meaningful patterns, trends, and insights.
• Demonstrated ability to communicate technical concepts and analytical findings clearly and effectively to both technical and non-technical audiences, including data specialists, software developers, and business stakeholders.
• Proven ability to work collaboratively within cross functional, agile, or product-oriented teams, contributing to data architecture, integration, and analytics discussions.
• Strong attention to detail, sound judgment, and a commitment to data quality, reliability, security, ethics, and responsible use of data and analytics.
• Ability to manage multiple priorities and contribute effectively in a fast paced, evolving technical environment, balancing data engineering deliverables with data science and modeling initiatives.