Software: Python | Big Data: Spark, AWS | ML: regression• Delivering machine learning and big data expertise to the climate change research team.• Use machine learning techniques to sufficiently improve existing heat-related mortality models, so that they can be used to provide predictions in funded future impact reports.• Utilise Spark on AWS to enable processing of terabytes of geospatial climate data in a reasonable time frame.• Develop geospatial transformation algorithms to re-grid and down-scale population data.

Software: Python, SQL | ML: classification, churn prediction• Improve the performance of existing churn prediction frameworks, for health insurance clients.• Add gradient boosted trees and neural networks to the classification model stack.

Developed and maintained a site access control system for a multinational construction company.

Software: Python, R | Big Data: AWS | ML: regression• Developed machine learning experiments to build accurate models to predict the effects of climate change on global mortality rates, labour-loss, and infant disease.• Designed multi-processing algorithms for single-node AWS instances, to process terabytes of simulated future climate and population scenario data.

Project Examples:Developed a social media listening system for a large utility company, to perform market segmentation on their clients, using various clustering analysis techniques.Collated data from several disconnected sources, to build customer churn prediction models, using K-Nearest Neighbour, Random Forest, and Support Vector Machine.Updated feature extraction and transformation algorithms, used to generate continuously evolving reports for the digital project manager.Developed a fraud detection system for insurance loss adjusters, where lost or stolen property claim details, were searched for on classified ads websites.Acting as Data Ambassador on several charity projects for DataKind Dublin. Involves liaising with the data owners, data carpentry, configuring APIs, and documenting in preparation for intensive data analytics sessions, involving teams of up to twenty data scientists.Scraped data on over 2 million products from an e-commerce website, and developed a price prediction engine, using neural network machine learning models.Implemented an ‘event detection’ algorithm to monitor and report on live Twitter action during the World Cup 2014 matches.Carried out extensive research on the suitability of using the MapReduce framework for implementing machine learning algorithms.

Project Examples:Developed a human resources solution for a civil engineering company taking on a new mining project in the South Pacific.Created a custom CRM system for a number of catering equipment suppliers.Introduced a team of solicitors to MS SharePoint / Office 365 and provided them with a case management system specific to the legal profession.

Project Examples:Document compliance management system for the extraction, transportation, and exportation of precious hardwoods, under tightly regulated government inspection.Multi line-item quotation system, detailing custom metal casting specifications imported from Synchro ERP foundry software.Resort management and home owners association portal allowing transparent reporting and collaborative decision making.Call tracking, inventory, and billing systems for a wireless internet service provider, interfacing with PRTG network monitor to raise alerts before emergencies occurred.

Project Examples:Managed the development and maintenance of a wireless network which provided internet service to eighty business and domestic clients in a challenging tropical environment.Trained and supervised a team of ten support technicians responsible for resolving customer and network issues.

Led a team involved in the development of insurance quotation applications.Acted as business analyst, liaising between the actuarial and sales departments.Developed quotation test systems to maintain quality assurance.