What are the responsibilities and job description for the Data Science Product Developer position at Entertainment Data Oracle (EDO)?
About Us
Entertainment Data Oracle (EDO) is a pioneering company that's changing the face of TV advertising. Our cutting-edge technology combines real-time engagement signals with advanced analytics, enabling marketers to optimize their campaigns and achieve remarkable results. With a presence in Los Angeles, New York City, and San Francisco, we're a vibrant community of innovators and thought leaders.
The Job Description
As a Machine Learning Engineer at EDO, you'll be part of our dynamic Data Science team. Your primary responsibility will be to design, develop, and maintain our internal data and modeling products. This will involve migrating our existing modeling frameworks to continuous training and monitoring, collaborating with cross-functional teams to diagnose and resolve issues with legacy models and pipelines, and leading high-impact projects that drive significant business outcomes. Key Requirements:
Entertainment Data Oracle (EDO) is a pioneering company that's changing the face of TV advertising. Our cutting-edge technology combines real-time engagement signals with advanced analytics, enabling marketers to optimize their campaigns and achieve remarkable results. With a presence in Los Angeles, New York City, and San Francisco, we're a vibrant community of innovators and thought leaders.
The Job Description
As a Machine Learning Engineer at EDO, you'll be part of our dynamic Data Science team. Your primary responsibility will be to design, develop, and maintain our internal data and modeling products. This will involve migrating our existing modeling frameworks to continuous training and monitoring, collaborating with cross-functional teams to diagnose and resolve issues with legacy models and pipelines, and leading high-impact projects that drive significant business outcomes. Key Requirements:
- 4-6 years of overall development experience.
- 3 years of Python experience writing clean, reusable code used by Data Scientists or deployed in production systems.
- Experience with MLOps, particularly with continuous model training and monitoring.
