Ph.D. or Master’s in Computer Science, Electrical/Computer Engineering, Industrial & Systems Engineering, Mathematics/Statistics, or related technical disciplines.
Proficient in programming in languages like Python, R, Java, or C++.
Proficient in algorithm design given various data structures including sparse matrices, sequences, trees, and graphs.
Strong working knowledge of machine learning including classification, clustering, and anomaly detection.
Experience in ETL, feature selections, hyper-parameter optimization, model validation and visualization.
Experience in tools like Scikit-Learn, Pandas, or XGBoost.
Experience in deep learning frameworks like Tensorflow or PyTorch.
Deep understanding and implementation experience of predictive modeling algorithms such as logistic regression, neural networks, forward propagation, decision trees and heuristic models, with familiarity dealing with trade-offs.
Experience in interfacing with other teams and departments to deliver impact solutions for the organization.
Self-motivated, independent learner, and enjoy sharing knowledge with team members.
Detail-oriented and efficient time manager in a dynamic and fast-paced working environment.