DescriptionA strong understanding of advertising and media data
sets, machine learning and deep learning model development as well as data
product development expertise will help set the stage for disruptive innovation
in the programmatic advertising space.
Mastery of Spark, Python, R as well as working knowledge in Tensor Flow, H2O Sparkling Water and Driverless AI, Anaconda Enterprise or other Jupyter Notebooks environments.
Graduate level academic background in statistics, econometrics, data science, computer science or applied sciences.
- 1-5 years relevant work experience in data science or related field.
- Machine learning and deep learning model development, a mastery of Spark, Scala, Python, R Studio as well as working knowledge in Tensor Flow, H2O Sparkling Water, Anaconda Enterprise or other Jupyter Notebooks environments.
- Familiarity with extremely large datasets, data structures and development platforms, including Hive, Hadoop and Pig, and experience working in an AWS distributed computing environment are all helpful.
- A foundational understanding of advertising and media data sets—television viewership datasets, mobile and desktop browsing, digital ad logs.
- Knowledge of identity graphs, graph theory, identity resolution, etc.—as well as a background in the mechanics of ad-tech targeting and delivery mechanisms will help ensure success.
- Graduate level study in statistics, econometrics, data science, computer science or applied sciences are preferred.
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