Daniel Learner Email & Phone Number

• Responsible for the data science relationship with Nike search engine optimization stakeholders
• Designed and built a data pipeline that processes millions of rows of daily data from multiple restful APIs. This improved data accessibility, automated reporting, and anomaly detection
• Developed customized methodology and analysis for client-specific digital marketing testing, measurement, and attribution
• Managed the transition of legacy data storage to the cloud (AWS and GCP)
• Introduced predictive, regression based models to client forecasting, enabling timely and better-informed decision making

• Managed digital marketing data science projects for client accounts in Finance, CPG, Telecommunications, and Retail each with a media spend of $25 million - $200 million annually
• Built a machine learning model (decision trees and logistic regressions) to produce daily conversion proxies for business analysts; increasing accuracy over the legacy methodology by 37%
• Mentored junior team members in both data science methodology and communication skills
• Led team that created a cross-channel media attribution model for a fortune 500 client

• Optimized a large financial client’s multi-million dollar search engine marketing and increased ROI by 80%
• Programmed in R and Python to automate complex and time intensive business analyst tasks
• Won global Digitas data visualization contest with a Bayes network representation of a client’s cross-channel marketing funnel

• Designed testing methodology for geo-targeting in paid search marketing
• Used Twitter API to provide local diurnal sentiment analysis

Master’S Degree, Computer Science

Bachelor Of Science - Bs

Education record