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RQ06209 - Data Analytical Specialist/Scientist - Intermediate
4 months ago
Responsibilities:
- 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
- Assist the Lead Developer with ETL and/or SSIS development where necessary
- 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
Knowledge Transfer
Transfer From Solution Development / Data Analytical Specialist/Scientist Junior 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.
Requirements
MUST HAVES;
- Candidate must provide a contact email address and be available to work this assignment.
- Experience with a range of analytical methods, techniques and tools such as statistical analysis and modelling, data mining, machine learning and algorithms, natural language processing, and other related disciplines
- Experience building visualizations in R, R Shiny, PowerBI, Cognos, or other tools
- Experience with ETL and SSIS development
- Experience with scripting such as Python, and languages such as DAX to be able to do trend analysis
- Experience developing BI and analytics
- Experience with creating dashboards and data visualization via Power BI or other visualization tools
- Experience with cleaning, transforming and visualizing data sets
- Advanced experience with SQL
- Demonstrated knowledge of emerging Business Intelligence trends and directions
- Experience with dimensionalized data/building cubes