Role Proficiency:
Interprets data and analyses results using statistical techniques under supervision

Outcomes:
Complies and assist in mining and acquiring data from primary and secondary sources; reorganizing the data in a format that can be easily read by either a machine or a person
Assist in identifying analyzing and interpreting trends or patterns in data sets' generating insights and helping clients make better decisions.
Conducts research on specific data sets to enable the senior analysts in their work
Assist in managing master data including creation updates and deletions.
Help developing reports and analysis that effectively communicate trends patterns and predictions using relevant data.
Provide support with technical writing and editing as required
Develop analytics to identify trend lines across several data sources within the organization
Assists senior analysts in examining and evaluate existing business processes and systems and offer suggestion for changes
Set FAST goals

Measures of Outcomes:
Schedule adherence on tasks
Quality – errors in data presentation and interpretation
Number of business processes changes highlighted due to vital analysis.
Number of stakeholder appreciations/escalations
Number of customer appreciations
No: of 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 it into a format which is consistent and analysable.

Analysis:
Use statistical methods to analyse data and generate useful results.

Create Data Models:
Use data to create models that depicts trends in the customer base and the consumer population as a whole

Create Reports:
Create reports depicting the trends and behaviours from the analysed data

Document:
Create documentation for own work as well as 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 like git
bitbucket
etc.

Quality:
Provide quality assurance of imported data
working with quality assurance analyst if necessary.

Performance Management:
Set FAST Goals and seek feedback from supervisor

Skill Examples:
Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching.
Communication Skills: Ability to present findings or translate the data into understandable documents
Critical Thinking: Ability to look at the numbers trends and data; coming up with new conclusions based on the findings.
Attention to Detail: Making sure to be vigilant in the analysis; coming up with accurate conclusions.
Quantitative skills - knowledge of statistical methods and data analysis software
Research skills: It is essential that applicants can undertake in-depth research quantify the information and produce qualitative and quantitative reports.
Mathematical Skills to estimate numerical data.
Work in a team environment
Proactively ask for and offer help

Knowledge Examples:
Proficient in mathematics and calculations.
Spreadsheet tools such as Microsoft Excel or Google Sheets
knowledge of Tableau or PowerBI
SQL
Python
DBMS
Operating Systems and software platforms
Knowledge about customer domain and also sub domain where problem is solved
Code version control e.g. git bitbucket etc.

Additional Comments:
Interprets data and analyses results using statistical techniques under supervision Outcomes: Complies and assist in mining and acquiring data from primary and secondary sources; reorganizing the data in a format that can be easily read by either a machine or a person Assist in identifying analyzing and interpreting trends or patterns in data sets' generating insights and helping clients make better decisions. Conducts research on specific data sets to enable the senior analysts in their work Assist in managing master data including creation updates and deletions. Help developing reports and analysis that effectively communicate trends patterns and predictions using relevant data. Provide support with technical writing and editing as required Develop analytics to identify trend lines across several data sources within the organization Assists senior analysts in examining and evaluate existing business processes and systems and offer suggestion for changes Set FAST goals Measures of Outcomes: Schedule adherence on tasks Quality – errors in data presentation and interpretation Number of business processes changes highlighted due to vital analysis. Number of stakeholder appreciations/escalations Number of customer appreciations No: of 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 it into a format which is consistent and analysable. Analysis: Use statistical methods to analyse data and generate useful results. Create Data Models: Use data to create models that depicts trends in the customer base and the consumer population as a whole Create Reports: Create reports depicting the trends and behaviours from the analysed data Document: Create documentation for own work as well as 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 like git bitbucket etc. Quality: Provide quality assurance of imported data working with quality assurance analyst if necessary. Performance Management: Set FAST Goals and seek feedback from supervisor Skill Examples: Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching. Communication Skills: Ability to present findings or translate the data into understandable documents Critical Thinking: Ability to look at the numbers trends and data; coming up with new conclusions based on the findings. Attention to Detail: Making sure to be vigilant in the analysis; coming up with accurate conclusions. Quantitative skills - knowledge of statistical methods and data analysis software Research skills: It is essential that applicants can undertake in-depth research quantify the information and produce qualitative and quantitative reports. Mathematical Skills to estimate numerical data. Work in a team environment Proactively ask for and offer help Knowledge Examples: