Championing the application of data to drive thought and influence strategic decisions. I am working and have worked on multiple research pieces that are of high priority to the business such as : • Building the most optional customer contact strategy that increases making optimal meaningful contact with a customer at the right time which results in an increase of sales. • Building a view of a customer's journey and identifying trigger points within that journey to design preventative measures for churn. Other things I am passionate about as part of my role: • Collaboration and building relationships across the business and other data teams by organising Monthly Analyst Meetings within the department. • Education of other non-technical members of the business on Data Science by hosting a regular Data Science Catch-ups. • Exploration of new tools and techniques that have potential to be beneficial in delivering Data Science projects more efficiently. - Successfully brought tools like Knime and Memgraph (graph database) into the team.

As a highly customer focused analyst, my main areas of focus were: • Running investigations into performance/drivers/variances and customer profiling by using techniques such as regression and cluster analysis. • Predicting future performance of the campaigns based on past performance by using techniques such as regression and random forest and decision trees in general. • Producing summary statistics on trading impact, rationale and commentary for departmental activities and recommending course correction actions. • Providing an assessment of value added/lost across the base each month and contribution of CVM activities.

Working at Thatcham Research, my role included : • Analysing the latest trends in motor claims and repairs, and continuous development of statistical models and forecasts/predictions to analyse the risks of autonomous vehicle technology. Modelling approaches mainly including GLM, Decision Trees, Random Forest and Bayesian, with an ever-increasing variety of techniques used. • Continuously researching and applying Bayesian Statistics (Multilevel modelling using Markov chain Monte Carlo simulations) • Analysing and manipulating Big data. • Working and sourcing statistical data for a variety of articles on the subject of autonomous driving and any driving related topics as part of BAU tasks.

As a young analyst at Ericsson I would enjoy: • Data and performance analytics. • Preparing KPI and SLA performance figures for the business and the customer. • Developing new performance indicators and insights for the business in order to help see broader pictures of project performance.

I thoroughly enjoyed this short but valuable experience, as I took part in completely different activities to anything I have experienced before, mainly : • Using various appraisal techniques for property development, project appraisals and evaluations. • Assisting stakeholders with decision making on projects.