Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelors Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics A Masters Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics. Preferred Qualifications: PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics At least 3 years of hands-on experience building, deploying, and maintaining high-scale, production-grade ML systems using MLOps practices, including AWS, Kubeflow, and CI/CD pipelines At least 4 years of experience in developing and optimizing state-of-the-art Deep Learning models, specifically Transformer-based architectures, using PyTorch and distributed training with multi-GPU optimization At least 4 years of experience with high-performance, distributed data processing for petabyte-scale feature engineering using frameworks like DASK and PySpark.