4+ years experience formulating complex business problems into actionable data solutions.
4+ years hands-on experience in building large scale ML systems to solve real world problems.
Master’s or PhD degree in Computer Science, Math, Statistics, Physics, Engineering or related level of experience required.
Strong communicator and experience with communicating complex ML outcomes to non-technical engineers.
Intuitive understanding of machine learning algorithms, supervised and unsupervised modeling techniques and their performance characteristics.
Experience working with large scale and real world datasets.
Experience with machine learning tools and libraries such as TensorFlow, Scikit-learn, R, Spark, PyTorch.
Experience with ML in manufacturing and operations spaces are pluses. In particular, working with extensive and messy manufacturing data set, as well as deploying production ready model to the factory.
Strong programming skills with 4+ years experience in Python for ML.
Experience with full-stack ML development (e.g., Flask, JavaScript) and productionalizing ML system using AWS.
Preferred Qualifications
Experience with Operations Research (OR) and linear & nonlinear constrained optimization.
Work experience in machine data (sensors, downtime, machine states, etc) for IoT & predictive maintenance applications.
Experience with manufacturing and supply chain ML use cases such as test optimization, cost reduction, and quality improvement.