Role Proficiency:
Entry level position with the primary responsibility of collecting data and basic analysis of results using statistical techniques.
Works under direct supervision.
Outcomes:
- Undertakes data collection from multiple sources; including primary secondary internal and external sources to generate relevant data for analysis.
- Assists in reorganizing the data in a format that can be easily read by either a machine or an p individual.
Assists in interpreting raw data.
- Compile data on Excel worksheets.
Assists in management and maintenance of database and master data.
This will include creation updates and deletions.
- Assist in developing reports using data that effectively communicate trends patterns and predictions using relevant data.
- Set FAST goals
Measures of Outcomes:
- Adhere to schedule on all tasks
- Quality: perform check for errors in data collection and presentation
- Timely update of databases and reports upon collection of new data points
- Number of insights generated for business decisions
- Number of all mandatory trainings completed
Outputs Expected:
Data Mining:
- Acquiring data from various sources
Reorganizing/Filtering data:
- Consider only relevant data from the mined data and convert into a consistent format to be analyzed.
Create Reports:
- Create reports depicting the trends and behaviours from the analyzed data
Document:
- Create documentation for own personal work product; perform peer review of documentation of others' work
Manage knowledge:
- Consume and contribute to project related documents
share point
libraries and client universities
Status Reporting:
- Report status of tasks assigned
- Comply with project related reporting standards/process
Code:
- Create efficient and reusable code.
Follows coding best practices.
Code Versioning:
- Organize and manage the changes and revisions to code.
Use a version control tool for example git
bitbucket
etc.
Quality:
- Provide quality assurance of imported data; work with Quality Assurance Analyst as needed.
Performance Management:
- Set FAST Goals and seek feedback from supervisor
Skill Examples:
- Analytical Skills: Basic knowledge of working with large amounts of data: facts figures and number crunching.
Basic knowledge of statistical methods and data analysis software
- Communication Skills: Ability to present findings or translate the data into understandable documents
- Critical Thinking: Ability to analyze numbers trends and data
- Attention to Detail: Ensure correct data and reports update
- Mathematical ability to estimate numerical data
- Work in a team environment
- Proactively ask for help when required
Knowledge Examples:
- Proficient in mathematics and calculations.
- Spreadsheet tools such as Microsoft Excel or Google Sheets
- Basic knowledge of Tableau or PowerBI
- SQL
- Python
- DBMS
- Operating Systems and software platforms
- Code version control e.g.
git bitbucket etc.
Additional Comments:
Role Proficiency: Entry level position with the primary responsibility of collecting data and basic analysis of results using statistical techniques.
Works under direct supervision.
Outcomes: Undertakes data collection from multiple sources; including primary secondary internal and external sources to generate relevant data for analysis.
Assists in reorganizing the data in a format that can be easily read by either a machine or an p individual.
Assists in interpreting raw data.
Compile data on Excel worksheets.
Assists in management and maintenance of database and master data.
This will include creation updates and deletions.
Assist in developing reports using data that effectively communicate trends patterns and predictions using relevant data.
Set FAST goals Measures of Outcomes: Adhere to schedule on all tasks Quality: perform check for errors in data collection and presentation Timely update of databases and reports upon collection of new data points Number of insights generated for business decisions Number of all mandatory trainings completed Outputs Expected: Data Mining: Acquiring data from various sources Reorganizing/Filtering data: Consider only relevant data from the mined data and convert into a consistent format to be analyzed.
Create Reports: Create reports depicting the trends and behaviours from the analyzed data Document: Create documentation for own personal work product; perform peer review of documentation of others' work Manage knowledge: Consume and contribute to project related documents share point libraries and client universities Status Reporting: Report status of tasks assigned Comply with project related reporting standards/process Code: Create efficient and reusable code.
Follows coding best practices.
Code Versioning: Organize and manage the changes and revisions to code.
Use a version control tool for example git bitbucket etc.
Quality: Provide quality assurance of imported data; work with Quality Assurance Analyst as needed.
Performance Management: Set