Description A strong understanding of advertising and media datasets, machine learning and deep learning model development as well as dataproduct development expertise will help set the stage for disruptive innovationin the programmatic advertising space.
Mastery of Spark, Python, R as well as working knowledge in Tensor Flow, H2OSparkling Water and Driverless AI, Anaconda Enterprise or other JupyterNotebooks environments.
Graduate level academic background in statistics, econometrics, data science,computer science or applied sciences.
- 1-5 years relevant work experience in data science orrelated field.
- Machine learning and deep learning model development, a mastery of Spark,Scala, Python, R Studio as well as working knowledge in Tensor Flow, H2OSparkling Water, Anaconda Enterprise or other Jupyter Notebooks environments.
- Familiarity with extremely large datasets, data structures and developmentplatforms, including Hive, Hadoop and Pig, and experience working in an AWSdistributed computing environment are all helpful.
- A foundational understanding of advertising and media data sets—televisionviewership datasets, mobile and desktop browsing, digital ad logs.
- Knowledge of identity graphs, graph theory, identity resolution, etc.—as wellas a background in the mechanics of ad-tech targeting and delivery mechanismswill help ensure success.
- Graduate level study in statistics, econometrics, data science, computerscience or applied sciences are preferred.
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