Data Scientist - Senior

Project Overview

The Ministry of Citizenship and Multiculturalism (MCM) is undertaking a digital modernization initiative to replace and enhance existing archaeology and heritage program capabilities with a modern, secure, scalable, and user-centred platform aligned to standards and enterprise technology directions. The initiative will modernize digital services, data management, and business processes to improve service delivery, information access, and decision-making across Ontario's heritage and archaeology programs.

Key Responsibilities

• Analyze complex data sets to generate predictive models and insights that inform business strategies
• Uses statistical methods, machine learning, and programming languages to interpret data and provide actionable insights
• Initiate, research, develop and manage new information studies and devise innovative statistical models for data analysis
• Conduct initial analyses to understand data’s characteristics and identify potential patterns or trends

Qualifications & Requirements

• Must be able to work 5 days onsite per week in Toronto
• Demonstrates knowledge of data analytics, including relational databases, geospatial analysis, spatial data management, data visualization, and analytical frameworks used to support business decision-making
• Demonstrates proficiency with analytics and visualization tools such as Power BI, Tableau, R Shiny, ArcGIS, or equivalent reporting and analytical platforms
• Demonstrates the ability to analyze, integrate, and interpret both spatial and non-spatial datasets to support planning, compliance, reporting, and decision-making activities
• Demonstrates the ability to develop and apply predictive models, analytical frameworks, business intelligence solutions, and geospatial analysis techniques
• Experience identifying business problems that can be addressed using data analysis
• Experience identifying relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables
• Familiarity and experience with data visualization tools e.g. Power BI
• Experience and proficiency with data mining, mathematics and statistical analysis
• Experience developing data-driven solutions to improve business performance and decision making
• Experience collaborating with cross-functional teams to integrate data insights into business strategies
• Extensive experience in pattern recognition and predictive modeling
• Extensive experience with programming languages like Python or R
• Experience working with big data sets
• Experience with code version control systems such as GIT
• Experience with database management systems
• Project management experience
• Awareness of emerging I&IT trends and technologies
• Excellent analytical, problem-solving and decision-making skills; verbal and written communication skills; interpersonal and negotiation skills
• A team player with a track record for meeting deadlines

• Advanced degree in social science or statistics
• Certifications such as the Data Science Professional Certificate (offered by IBM) or Google Data Engineer certification

Technical Knowledge / Skills - 50%

• Demonstrates knowledge of information management, data management, database architecture, data governance, metadata management, master data management, data lineage, extract/transform/load (ETL) processes, data warehousing, and data integration.
• Demonstrates knowledge of data modernization, digitization methodologies, records conversion, data quality improvement practices, and the management of structured, semi-structured, unstructured, historical, and legacy datasets.
• Demonstrates proficiency in statistical analysis, data mining, predictive analytics, artificial intelligence, machine learning, research methodologies, and data modelling techniques.
• Demonstrates knowledge of data analytics, including relational databases, geospatial analysis, spatial data management, data visualization, and analytical frameworks used to support business decision-making.
• Demonstrates proficiency with Structured Query Language (SQL) for accessing, extracting, transforming, and analyzing data across multiple platforms and repositories.
• Demonstrates proficiency using Python, R, or other equivalent tools for data analysis, modelling, automation, and data transformation.
• Demonstrates proficiency with analytics and visualization tools such as Power BI, Tableau, R Shiny, ArcGIS, or equivalent reporting and analytical platforms.
• Demonstrates knowledge of information management standards, data governance frameworks, accessibility requirements, and applicable GO-ITS standards.

Research, Analytical and Problem-Solving Skills - 40%

• Demonstrates the ability to analyze and assess complex datasets to identify data quality issues such as duplicate records, inconsistencies, missing values, and invalid data.
• Demonstrates the ability to support data migration, digitization, modernization, and information management initiatives through data analysis and quality assessment…