Associate Iii

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:

- Bayes Theorem, conditional probability, Dependent/Independent Events, Random Variable, Probability Distributions, Statistical Test - Language
- Python/Fonduer - Data Analysis
- MongoDB, PLSQL