Vice President Marketing Analytics
Job ID: EB-8837361019
Category: Analytics & Data Sciences
Location: New York, NY
This is an exciting time for the company, and data and analytics is at the center of it. The Group is leveraging data, research and advanced analytics to amplify & evolve the core business, exploit growth opportunities and foresee risks.
Responsibilities include but are not limited to conversion and activation rates, lifetime value, channel analytics from digital to call-center (inbound, outbound, customer care), offer and campaign performance, retention analytics, subscriber forecasting, performance, and general KPIs to measure the overall health of marketing activities and the business as a whole.
This is a significant role in the organization as both the marketing analytics COE lead and representative to all levels of the organization including frequent interaction with top leadership. All lines of business depend on this team for marketing analytics and insights to drive their business forward and foresee risks before they impact the business.
• Master’s degree or PhD in statistics, business analytics, predictive analytics, economics, MBA, science, or other quantitative focus preferred
• Minimum of 10-15+ years relevant direct/database marketing analytical experience in a leadership position.
• Ability to build and execute a vision for continuous improvement of analytical capabilities and efficiency.
• A natural intellectual tenacity combined with strong statistical, analytical and problem-solving skills.
• Proactive leader with the initiative to constantly search for new ways to impact the business and who takes ownership of responsibilities.
• A results-oriented leader with a track record of driving real business impact through analytics.
• Required expertise in: SQL, large database platforms (e.g., Teradata, Vertica, Hadoop, Hyperion Essbase / Cognos), Expert Excel, Strong PowerPoint, Microsoft Office products.
• Desired expertise in: Cloud platform solutions (e.g., Azure, AWS, Google), Predictive Analytics and Machine Learning, segmentation (cluster analysis), Visualization tools (e.g., Tableau, Qlik), Data Science Tools (Python, R, JMP, Weka).