Analyze and monitor data from factory equipment to improve yield, capacity, and efficiency through technologies including but not limited to:

- Machine Learning (ML)

- Reinforcement Learning (RL)

- Equipment Parameter Tuning

- Predictive Health Monitoring (PHM)

- Design of Experiments (DOE)

- Statistical Process Control (SPC)

- Operations Research (OR)

Job Requirements

- Python, SQL

- Sklearn, Pandas, Numpy, etc.

- Pytorch, Deep reinforcement learning

- Proficiency in statistical analysis, time series, anomaly detection, signal processing and spectrum analysis, etc.

- Experience with version control tools such as Git and Docker

- Practical experience with SPC and DOE implementation.