Data Analyst

The person should interact directly with senior-level business executives of the client organization and understand the business requirements, collate, understand, and analyze the data, and prepare/build reports / automated dashboards. The reports / automated dashboards will be a judicious and effective mix of numerical tables (including appropriate statistical measures) and visualizations through charts/diagrams. The representation might require (re)defining metrics / KPIs or suggestions to the client about inadequacies in the data if such is the case. It might also involve some amount of data cleaning / preprocessing and merging / integration from different sources.

Advanced-Level skills with MS Excel, including basic statistical analysis and visualization, lookup, Pivoting, conditional formatting, etc. Some skill with macros and/or scripting is desirable.

Working-Level skills with at least any one of Tableau or MS Power BI including statistical analysis, geospatial representation of data, and connecting to multiple data repositories (like RDBMS, CSV files, etc.). Must have skills in creating automated dashboards

Working-level skills with MySQL (preferred, or other RDBMS) and writing SQL queries (select using primary and foreign keys, merge, joins, etc.) as well as some GUI front-end tools like MySQL Workbench or phpMyAdmin

Working-level skills with at least one GUI-based or workflow-based statistical / analytics tools from the following: SPSS, Minitab, R Commander, KNIME, Altryx

Working-level skills in BI reporting / statistical/mathematical / data science-related programming in either R or Python. Some basic-level skills in visualization/graphics libraries (like ggplot2, plotly, etc) and front-end app frameworks (like R Shiny and/or Python Dash) is desirable and will be preferred

Fluent and excellent oral and written communication skills in English

Work in cross-functional teams involving both technical and non-technical members and stakeholders

Translating business requirements to technical requirements and explaining the outcome of technical analysis in an easily comprehensible manner to non-technical clients

Self manage work planning and time management to complete tasks / projects on time with excellent quality

Between 12 and 24 months in a full-time data analyst/analytics position applying most of the skills as indicated above

Academic Qualification:

Minimum undergraduate degree from a reputed university, preferably in STEM subjects or in Economics.

Selection Process:

Personal interview with a strong emphasis on technical knowledge. It is highly desirable that the candidate is able to demonstrate some of his/her past work in the requisite skill areas.