They will be responsible for their production grade signal generation and ML systems. They can act as data scientists, but should be comfortable pushing their algorithms, models, and signals into production.
Strong understanding of statistical analysis and computational modeling.
Strong understanding of algorithms and data structures.
Familiar with map reduce and big data processing (Spark, Hadoop, DataFlow, etc).
TensorFlow (or another GPU integrated deep learning library).
Deep understanding of machine learning algorithms.
Deep understanding of numerical optimization.
Strong understanding of data structures and algorithms.
Plus, but not required:
Previous experience in tech industry (GOOG, AMZN, FB, NFLX, Spotify, etc).
Experience building industrial grade ETL pipelines.
Experience building frontend systems.
Familiarity with dashboards and other visualization tools.
Ability to derive generalization bounds for common ML algorithms.
Experience developing new machine learning algorithms.