I lead a team focused of measurement and forecasting of payments customer support. We own a large metric suite across multiple channels and provide forecasting for headcount required to ensure support runs at optimal cost and without backlogs.

As an IC5 payments data analyst in Risk & Payments, I own and develop a suite of metrics to inform business stakeholders of support/payment performance. My focus is on measurement and forecasting of support demand. I ensure the we have full metric coverage across our support systems and work to develop novel metrics to enhance measurement of support.The role involves ownership of metric definitions, communication with leadership, development and maintenance of pipelines/dashboards and collaboration with XFNs.

I delivered insights for high value clients in the DACH market by leveraging member data. This was a client facing role where I was responsible for developing narratives from ideation stage to presentation to clients. I was also involved in several insights projects to enhance our data, automate insights and scale globally.

As part of the analytics innovation team I developed novel systems in the areas of journey analysis, lead generation and fraud detection.

Technologies used: java (spring), ruby and chefI worked as part of a team developing monitoring software for services hosted in IBMdatacenters. Our software generated real time data which was then processed and analysed by data analysts to measure service performance and detect outages.

During this contract I was working on the HIV Mutation browser (HIVMut.org), a webapp which catalogues HIV mutations extracted from literature using text analysis methods. The role involved a combination of software engineering, data analytics and advertising to the end users.Main Duties:* Making improvements to the text analysis pipeline (bash and perl) and web interface (php, HTML, javascript).* Promoting the service among the HIV research community.

I developed software and machine learning tools to investigate the impact of changes in torsion induced by changes in secondary structure states. I used a bidirectional recurrent neural network to create a predictor of polyproline II secondary structure.Technologies used: neural networks, python, R, bash, and high performance computing on ICHEC clusters.

My project was both computational and lab based. The computational component involved the application machine learning (Neural networks, regression and random forests) methods to protein motif discovery. I was also involved in several data mining projects.As a side project I also developed the FightMalaria@Home project. This project aims to discover novel drugs to treat malaria and to find the targets of existing drugs in an effort to understand and combat malaria drug resistance.

During my PhD I worked as a demonstrator for bioinformatics modules and as a tutor/lecturer for a post graduate module in linux, database fundamentals and web services.

Personal Responsibilities:- Development and maintenance of installation software.- General programming tasks using Ant, Groovy and Java.- Web application testing using Selenium