Data Analytics

Communication with stakeholders to get data requirements, improve reliability and accuracy of data-driven product and present the insights.

Cleaning the data, checking the quality, accuracy and security of the data.

Creating dashboards with important insights to support business decisions.

Data Science

Creating advance statistical measures such as outlier detection, predicted values, geographical angles.

Performing geo-spatial analysis and demographical clusters to select products and services for particular groups.

Creating machine learning models such as time series forecaster, classification techniques and optimising business processes.

Analytics Engineering

Connecting raw sourcing data into a single table.

Scheduling queries to collect fresh data on the go.

Maintain data documentations and definitions.

Apply software engineering best practices to analytics code.

Optimising SQL code to save on execution time and data storage.