Senior Analyst / Data Scientist
Columbus, Ohio, United States
Data Leadership- Spearheaded K-means clustering model of prospects based on linked activities within a dataset of 120MM pageviews per month. Information was used to guide audience targeting and business planning leading to increase in sales conversion rate of 7%. - Built data science intern program and guided interns to produce actionable analysis.- Led the analytics team through the selection of long-term projects and the most efficient modeling methodology.In-Depth Marketing Analytics- Developed machine learning models using multiple data sources (sentiment, customer data, large scale traffic information) to determine presales cycle placement to focus company on the right contact at the right time. - Provided answers to core business questions using Google BigQuery to tie together complex datasets, including full views of prospect activity prior to purchase. - Created and updated flexible attribution model using massive hit-level traffic data leading to increased awareness of how prospects become customers. - Used statistical models to determine the effectiveness of new customer acquisition channels, including direct mail, radio, and partner sources, leading to quickly optimized marketing spends. Product Analytics- Rebuilt on-site recommendation engine using machine learning and statistical models leading to 15% increase in page depth. - Improved call center sales conversion by 9% through in-depth salesperson analysis.- Constructed advanced customer cohort analysis leading to 27% improved customer retention. - Partnered with the product and development teams to construct analytical framework around new customer social tools. Technology Early Adopter- Early adopter of reactive automated data visualizations through R Shiny giving flexible and automated data access to all stakeholders.- Incorporated Github into analytics coding development aiding in coding efficiency and ability to pursue deeper trends.