Job Description :

• Possess strong writing, data visualization and communication skills with the ability to communicate complex quantitative analysis in a clear, precise, and actionable manner to senior leaders and stakeholders
• Good understanding of foundational statistics concepts and algorithms: linear/logistic regression, random forest, boosting, Neural Networks, etc.
• Ability to access, manage, transfer, integrate and analyze complex datasets, especially using SQL or map-reduce techniques
• Familiarity with libraries such as SparkML, Tensorflow, scikit-learn, or others
• Broad understanding of the technologies and capabilities of Machine Learning and Deep Learning
• Familiarity with style-transfer learning, unsupervised learning, training sets, and inference models
• Experience developing, training, and evaluating deep-learning models using public deep learning frameworks (e.g. PyTorch, TensorFlow, and Keras)
• Experience in deep networks (CNN, DBN, RNN, LSTM, DCN) or reinforcement learning (RL)
• Strong understanding of machine learning algorithms and principles