Working in Python/Django as part of supporting and improving our innovative Business to Business (B2B) platform for matching companies with Suppliers of Equipment and Containers

Implemented methods to generate generic foreign key tags for emails based on key parameters and store emails in S3 for the purpose of A|B testing

Implemented infrastructure for monitoring key statistics related to SEM efficiency and synching data between our internal databases, 3rd party marketing system, and 3rd party sales tracking system via API calls.

Technical lead and developer on $250K sales team optimization application for top-5 banking client.

Inputs includes hundreds of GB of transactional data, CRM system data, real-time market data; output is suggested financial products for sales team to present to institutional investors.

Final model had dramatically improved recall and precision over baseline model used by client, and the application is currently helping sales advisors in the Asian and European markets.

Technology Stack: Python, C++, Linux, proprietary real-time analytics platform, AWS; Git and SVN for collaborative code development, testing, and validation in agile development environment.

Technical lead on all projects within the asset management vertical focusing on the utilization of transactional and demographic data to develop predictive models for the sales and marketing of emerging funds to financial advisors. Models developed during these projects are in use by some of the largest asset management firms in US.

Project manager and team leader for several projects focused on using behavioral data to better target marketing and optimize the efficiency of our clients’ customer relationship management systems

Worked with development and modeling teams to optimize our proprietary scoring algorithm by incorporating mutual information and isolating high value behavioral and demographic parameters most associated with future sales

Led the analytics and implementation of a $500K project for a major telecommunications company to improve their prospecting and client retention through use of SQL, logistic regression, and predictive scoring