This project was first idealised from the growing interest in data science and machine learning industry. We aimed to build a proof of concept platform to solve multiple use cases.

The use cases that we initially decided on were:

• Customer segmentation for retail with recommender system.

• Smart Meter Engineer best route recommender system.

Developed data processing workflows to generate clean and refined predictive data outputs.

Created numerous solutions within a single resilient framework.

This project was delivered using the Scrum Agile Methodology.

This team included 2 data engineers/consultants as well as 3 data scientists and a Scrum Master.

I played the role as the data consultant assisting in the build of the platform but overseeing the work of the data scientists that we had outsources from Pivigo.

After partnering with Object Oriented Machine learning tool RapidMiner, we utilised this software on the AWS cloud development environment (workspace).

Implemented various machine learning algorithms to enhance predictive modelling capabilities. For example, linear regression, clustering, Naiive Bayes theorem and Neural Nets.

Optimized model parameters to ensure accurate predictions and reliable results.

Utilised Talend Data Integration to extract and cleanse data from open sources, such as geographical, weather or event data, to build the advanced analytics platform.