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- Passion for learning and innovating new methodologies at the intersection of applied math / probability / statistics / computer science. Proficient in translating unstructured business problems into an abstract mathematical framework.
- Fluency in python, R, SQL.
- Experience in creating ML models using ML techniques like Xgboost, random forest, etc.
- Experience in AWS using services such as EMR, ECS, S3, EC2, Comprehend, SageMaker.
- Spark or Pyspark experience preferred.
- Ability to initiate and drive projects to completion with minimal guidance.
- Ability to communicate the results of analyses in a clear and effective manner.
- Ability to deliver prototypes in both Jupyter or Zeppelin notebooks, as well as creating packages for cross-team utilization that can be invoked via pip install
- Preferred experience with tools such as H2O, SparkML, TensorFlow, Keras.
- Above average capabilities with cloud computing techniques or tools such as Docker, Gitlab CI, Python packaging, command-line executions and shell scripting.