Director of Data Science

Magnetic is a technology company with a marketing platform for enterprises, brands and agencies. Our prospecting, remarketing and merchandising solutions help marketers find, keep and bring back customers across channels and devices. These solutions are powered by our unique data including purchase intent and behavioral insights.

As a Director of Data Science, you will oversee the Data Science team. You will guide and support teammates in using machine-learning techniques and building algorithms in multiple areas including predictive modeling, recommendations, fraud detection and NLP. You will work with mix of open source and in-house developed tools such as Samza, Spark, Hadoop Map-Reduce, Impala, Vowpal Wabbit, and MLLib. We’re looking for you to help us define the best-of-breed tool set, so we expect this list to change over time.

* Leading team of Data Scientist to improve performance of our marketing and online advertising platform * Leveraging your Data Science background to guide research and development of our modeling and categorization algorithms * Developing algorithms using Python, Java, and/or Scala * Collaborating with engineering to understand what’s currently possible, and what might be possible in the future * Speaking at conferences, writing and contributing to scientific papers, and encouraging others to do the same

* You have drive to unlock the true power of big, noisy, messy, real-world data * You have extensive applied research or industry work experience in the online advertising, marketing technology, social or e-commerce, or retail spaces * You have managed teams of Data Scientists, and believe they’re best motivated when they actively participate with the results of their work in production * You have experience working with multi-terabyte-sized data sets * You have worked with modern big-data friendly data science tools, such as those we’ve listed above * You know how to evaluate speed vs. quality tradeoffs in machine learning models * You have PhD or equivalent experience in a highly quantitative field