· Data science background and experience manipulating/transforming data, model selection, model training, cross-validation and deployment at scale.
· Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and Torch.
· Experience with statistical/mathematical software (e.g. R, Weka, SAS, Matlab)
· Proficiency with programming languages such as Python, Scala and R
· Experience with NoSQL is strong plus
· Experience with AWS services related to AI/ML highly desirable, particularly Amazon EMR, AWS Lambda, Machine Learning, AWS IoT & Greengrass, Amazon DynamoDB, Amazon S3, Redshift, Amazon EC2 Container Service, etc.