Responsibilities:

• Lead the development and delivery of functional analytics to support evidence-based decision-making and produce actionable insights
  
• Work closely to assess current data analytics and reporting capabilities, gather future-state requirements and identify further opportunities for improvement
  
• Facilitate decision-making and manage client expectations
  
• Own the execution of analytics initiatives including end-to-end reporting and data set delivery
  
• Participate in documentation, development, testing, and end user training
  
• Work with functional area experts, Data Architects and stakeholders to understand complex business issues and develop appropriate Business Intelligence solutions
  
• Build data models that provide information which is accurate, easy to understand and unbiased
  
• Communicate complex quantitative analysis in a clear and precise manner, providing useful visuals and summaries
  
• Provide interpretation, advice, and expertise to client groups and other stakeholders, including direction on how to transform analytics into actionable information and proactive insights that support decision-making
  

General Skills:

• Excellent analytical, problem-solving and decision-making skills, verbal and written communication skills, interpersonal skills and teamwork skills
  
• Outstanding consulting and relationship management skills, with proven ability to elicit requirements, develop/consult on options and solutions, and provide effective guidance
  
• Adept at communicating to both technical and non-technical audiences
  
• Experience with a range of analytical methods, techniques and tools such as, but not limited to: statistical analysis and modelling, data mining, and other related disciplines at the specified experience level
  
• Ability to manipulate and analyze complex, high-volume data from structured and unstructured sources
  
• Experience developing data extraction, transformation, and load functionality for large relational and multi-dimensional data stores
  
• Experience designing high quality interfaces to present information in a meaningful way to end users
  
• Broad understanding of data management, financial and business analysis, database architecture, and information visualization
  
• Proficiency in query languages and experience constructing complex query statements
  
• Experience in one or more programming or scripting languages
  
• Strong investigative and logic skills
  
• Proficiency in mathematics and statistics
  
• Awareness of emerging Business Intelligence trends and directions
  
• Functional area experience as required
  
• Experience with analytical software such as R, PowerPivot, Matlab, SPSS, or SAS an asset
  
• Proficiency with desktop analysis software including Microsoft Excel, Access, VBA
  
• Proficiency with Power BI data visualisation tool
  

Key responsibilities for this role include, but are not limited to the following:

• Manipulate and analyze complex, high-volume data from structured, unstructured and semi-structured sources, and multi-dimensional datasets with a variety of tools
  
• Identify and assess information, data needs and requirements to support business plans/practices and business goals/objectives
  
• Analyze data in source systems to identify data quality issues (e.g., missing values, duplicate meanings, and invalid data)
  
• Develop complex SQL queries to extract, analyse and validate key business data from a wide range of data repositories (relational and multi-dimensional data stores (Oracle and MS SQL Server), flat files, structure and unstructured)
  
• Use creative thinking and propose innovative ways as it relates to data mining, behavioural economics, statistics and statistical models, algorithms, data integration, information management, predictive analytics and analytics modeling, and data-related information technology
  
• Provide planning advice to the project team on the use of data, and building capacity on performing advanced analytics and data analysis;
  
• Provide advice and guidance to the project team on data de-identification to minimize privacy risks
  
• Creating and/or updating data processing overview, technical design, source to target mapping, operation manual and other technical documentation;
  

Knowledge Transfer

Transfer From Data Analytical Specialist/Scientist – Senior to Project Manager

When Knowledge Will Be Transferred:

• Knowledge transfer must be completed one week prior to the end of the project or one week prior to the consultant leaving the ministry.
  

What Knowledge Will Be Transferred:

• All deliverables, including design/supporting/release/training documents must be checked into designated version control repositories (for example, SharePoint). All final documents and working drafts related to project requirements or solution design must be stored on designated project repositories (for example, SharePoint site, HPQC, TFS, Azure DevOps)
  
• Project manager and designated ministry staff must be regularly informed in writing (by email) of where documentation has been stored and must be provided a minimum of one walk-through of all documentation as part of the final knowledge transfer activities.
  

How Knowledge Will Be Transferred:

• Knowledge will be transferred through 1 on 1 sessions, emails, document updates and document review with the team.
  

MUST HAVES:

• Demonstrates efficiency in Structured Query Language (SQL) to access databases to conduct research and use applications to retrieve and manipulate data from databases located on different platforms. (modelling analytics and visualization tools)
  
• Experience with multiple databases (e.g. Oracle MS-SQL) and proficiency with various modeling, analytics and data visualization software tools (PowerBI, etc.)
  
• Demonstrate knowledge of data skills, methods, techniques, and tools, including data mining, statistical analysis and statistical models
  
• Ability to analyze data in source systems to identify data quality issues (e.g., missing values, duplicate meanings, and invalid data)
  
• Use creative thinking and propose innovative ways as it relates to data mining, behavioural economics, statistics and statistical models, algorithms, data integration, information management, predictive analytics and analytics modeling, and data-related information technology
  

Nice to Have:

• Experience with multiple databases (e.g. Oracle MS-SQL) and proficiency with various modeling, analytics and data visualization software tools (PowerBI, etc.)