Senior Business Intelligence Manager

Zeta Global•New York, NY

21d•Hybrid

About The Position

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com. Zeta Global seeks a Senior Business Intelligence Manager in New York, NY to write and test SQL queries and analysis.

Requirements

Bachelor’s degree in Engineering Management, Engineering or Data Science plus 5 year of experience.

Responsibilities

Use SQL queries to translate business requests into reports.
Provide internal groups with data and tools needed to optimize their initiatives.
Demonstrate performance of system to clients via custom reports.
Maintain and improve predictive queries.
Identify opportunities for revenue and campaigns.
Implement Monetization Strategies via analysis and queries built on top of operational logs and reporting.
Create and maintain aggregations for internal and external use.
Work with the Campaign Operations team to create alerts when changes of performance and troubleshoot setup.
Use tools and systems such as RedShift, Athena, Looker, Druid, Airflow, and Application User Interfaces to pull reports.
Use SQL (Postgres or other).
Write code in R/Python.
Run queries against production systems.
Use statistical concepts such as confidence intervals, t-test, z-tests and sampling distributions.
Handle incremental or A/B testing and hypothesis testing/model building with linear/logistic regression.
Interact with product to create a reasonable balance between product roadmap and iterative improvements to data pipelines and data processing tasks.
Monitor costs and implement changes to ensure cost-effective processes for newly developed features and through continuous review of existing processes.