Role Proficiency:
Independently interprets data and analyses results using statistical techniques

Outcomes:
Independently Mine and acquire data from primary and secondary sources and reorganize the data in a format that can be easily read by either a machine or a person; generating insights and helping clients make better decisions.
Develop reports and analysis that effectively communicate trends patterns and predictions using relevant data.
Utilizes historical data sets and planned changes to business models and forecast business trends
Working alongside teams within the business or the management team to establish business needs.
Creates visualizations including dashboards flowcharts and graphs to relay business concepts through visuals to colleagues and other relevant stakeholders.
Set FAST goals

Measures of Outcomes:
Schedule adherence to tasks
Quality – Errors in data interpretation and Modelling
Number of business processes changed due to vital analysis.
Number of insights generated for business decisions
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 depict 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 and 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 an understandable document
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 to come with accurate conclusions.
Quantitative skills - knowledge of statistical methods and data analysis software
Presentation Skills - reports and oral presentations to senior colleagues
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
Advanced 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:
NA