Data Scientist - Senior

Job Title: Data Scientist - Senior

Location: Toronto

Work Model: Onsite

Duration: 11 months

Extension: 1 Time

Must Haves

• 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.

Description / Responsibilities / Skills

Description

• Ministry of Citizenship and Multiculturalism (MCM) is undertaking a digital modernization initiative to replace and enhance existing archaeology and heritage program capabilities
• 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

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

Experience & Skill Set Requirements

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 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 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 activities.
• Demonstrates the ability to identify, assess, and document business data requirements and translate them into analytical solutions.
• Demonstrates the ability to identify trends, patterns, relationships, and insights within large and complex datasets to support business, program, and regulatory objectives.
• Demonstrates the ability to integrate data from multiple sources and provide recommendations that support evidence-based decision-making.
• Demonstrates the ability to apply innovative analytical approaches, emerging technologies, and industry best practices to address complex business challenges.

Communication and General Skills (10%)

• Demonstrates strong verbal and written communication skills, including the ability to communicate complex analytical findings to technical and non-technical audiences.
• Demonstrates the ability to prepare technical documentation, business reports, data dictionaries, source-to-target mapping documents, and data flow diagrams.
• Demonstrates the ability to collaborate effectively with business stakeholders, information management specialists, GIS specialists, business analysts, project teams, and technical resources.
• Demonstrates the ability to communicate analytical and geospatial findings through reports, dashboards, maps, presentations, and other visualization tools.
• Demonstrates the ability to facilitate discussions, present recommendations, and support informed decision-making.
• Demonstrates the ability to work effectively within multi-disciplinary teams in a complex project environment.