Skills Required:

Python Programming, SQL Proficiency, Machine Learning (Model Development & Application), Predictive Modeling, Statistical Analysis, Data Visualization (Power BI/Tableau/ArcGIS), Geospatial Analysis & Spatial Data Management, Communication (Technical & Non-Technical Audiences), Apache Spark, Data Quality Assessment, Data Governance & Management, ETL Processes & Data Integration, Git Version Control, Business Requirements Translation (to Analytical Solutions), R Programming

Job Description:

HM Note: This onsite contract role is in office every day at the manager's discretion. Candidate resumes must include first and last name, email and telephone contact information.

Description

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

General Skills

- 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⁢ 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

Desirable Skills

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



or Google Data Engineer certification

Skills

Experience and 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 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 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 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.
- 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 robust 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.

Must Have:

- 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.

📌 Data Scientist (Toronto)
🏢 Foilcon
📍 Toronto