Job Location: Toronto (Hybrid)
Job Duration: Long-Term ContractOne of our Government clients is looking for a Senior Data Analytical Specialist/ScientistJob DescriptionResponsibilities
Lead the development and delivery of functional and ministry-specific analytics to support evidence-based decision-making and produce actionable insights
Work closely with client's groups 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
Develop robust statistical models and machine learning algorithms to model business scenarios and extract valid inferences
Participate in documentation, development, testing, and end user training
Work with functional area experts, Data Architects and ETL Developers and stakeholders to understand complex business issues and develop appropriate Business Intelligence solutions
Design methods to capture, structure, transform, and process data to be used to generate models
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 team work 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, machine learning and algorithms, natural language processing, 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
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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 within the Ministry on performing advanced analytics and data analysis;
Provide advise 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)
- 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.
- 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.
- Demonstrate knowledge of data skills, methods, techniques, and tools, including data mining, statistical analysis, statistical models and algorithms on machine learning, deep learning, natural language processing, artificial intelligence and other related disciplines
- 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 coding skills in various data languages (e.g. R, Python) and proficiency with various, modeling, analytics and data visualization software tools (R Shiny, PowerBI, etc.)
Technical Knowledge/Skills - 50%
- Demonstrate knowledge of information management, data management, financial and business analysis, database architecture, and data related concepts such as data preparation, data integration, data anonymization, data extract/transform/load (ETL), data warehousing, data lineage, metadata management, master data management, and data governance
- Demonstrate knowledge of data skills, methods, techniques, and tools, including data mining, statistical analysis, statistical models and algorithms on machine learning, deep learning, natural language processing, artificial intelligence and other related disciplines
- 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.
- Experience with coding skills in various data languages (e.g. R, Python) and proficiency with various, modeling, analytics and data visualization software tools (R Shiny, PowerBI, etc.)
- Experience in the use of data modelling methods and tools (e.g. PowerDesigner) including a working knowledge of metadata structures, repository functions, and data dictionaries
- Understand legislative regulations, policies and guidelines, ministry programs/services and policy development processes, data standards (e.g. GO-ITS) and privacy legislation (e.g. FIPPA) related to access and release of personal information and data
Research, Analytical and Problem-Solving Skills - 40%
- Ability to analyze data in source systems to identify data quality issues (e.g., missing values, duplicate meanings, and invalid data)
- 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
- 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
General Skills - 10%
- Communication skills to prepare technical and non-technical status reports, planning documents, and operational policies, and provide explanations on data issues and complex data analyses
- Writing skills to prepare technical specifications, source to target mapping document and data process flow diagrams
- Demonstrate experience working in a multi-team environment spanning across business and IT stakeholders in the pursuit of common missions, vision, values, and mutual goals.
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