Responsibilities

1. Auctioning algorithms and understanding ad exchanges

2. Observing and manipulating the data and trying to understand what is happening

3. Recognizing problems, formulating problems, and leading the effort to solve the issues

4. Implementing algorithms, knowing and understand the following:

5. Python/Scala + Tensorflow/Caffe

6. Spark/Samza/Flink

7. Druid/Cassandra/Redshift

8. Probabilistic methods/Variational Autoencoders/Deep learning

 Requirements

1. Data Scientist by experience and education

2. PhD/MSc in Machine Learning, math, or computer science

3. Experience making different kinds of prediction and automated decision-making algorithms

4. In-depth experience with one or more of the following fields:Feature extraction or synthesis and detecting event or behavioral patterns. Classification/prediction with logistic, network models, or other models applied to a massive scale.