Manager of Data Science and Customer Insights (Marketing) Oct 2007 – Present• Applying my business and technical background to follow the agile framework within the CRISP-DM cycle to provide data driven solutions to complex business problems: business and data understanding, data preparation, model development and deployment, and finally, evaluation and improvement• Delivered a 39:1 ROI in a recent data driven 2018 initiative to generate sales opportunities• Lead a team of Data Scientists in the development, benchmarking and selection of supervised and unsupervised models like Gradient Boosting, Naïve Bayes, Random Forests, SVM, K-Means Clustering and regression, and other appropriate data mining solutions like Association analysis and Time Series forecasting• Responsible for Cisco’s America’s Marketing and Salesforce Contact strategy to ensure Sales and Marketing’s access to rich and accurate contact data:o Maintain multiple vendor relationships to ensure optimal use of the quarterly six figure budgeto Remain current on available solutions to further improve and automate the validation of existing, and the addition of new contacts, e.g. the integration of third party API’s into Cisco’s Tech Stacko Manage a group of analysts in the day to day operations and implementation of the Contact Strategyo Perform strategy and planning, providing regular communication and recommendations to Senior Leadership • Maintain a text based SVM learner to classify individuals into categories which are crucial to Cisco’s ability to personalize marketing journeys• Heavy expertise in R, Python and SAS in conducting data mining, model development and read-write communication with the Hadoop cluster• Continuous Personal Development:o In Year 3 of Cisco’s Data Science program provided in conjunction with UNC and UC Irvineo Currently in Stage IV of Cisco’s internal Leadership programo External subscription with Data Camp

- Lead Analyst to a major Health Insurance client - providing scheduled and ad hoc reporting, through coding within Base SAS - Used Regression and Ordinary Least Squares analysis to create models used to identify contacts that were "Most likely to Respond" and "Most likely to Convert" - higher decile contacts then received higher value Marketing pieces - Major part of the successful pitch for the business of a national retail outlet - created multiple dashboards through Crystal X-Celsius, used in the pitch - Consulted on all data related decisions - investigating and integrating appropriate analysis tools, across multiple client data

- Developed coding algorithms to extensively mine internal business and consumer data - Generated scheduled and ad hoc reporting used for critical business decisions - Used Predictive Modeling to identify customers with a high risk of switching to competition, so that they could be targeted for Retention - Managed and nurtured the development of a Junior Analyst - High Level expertise in Base SAS, SAS Enterprise Guide and Miner, Microsoft Suite including Excel and Access -