Designs, configures, develops, tests, and supports informatics and data science solutions for a wide array of technical use cases; Applies analytical methodologies to diagnose data-related challenges, implement solutions, and evaluate performance; Documents and presents requirements, design alternatives, and findings to team members and clients; Ability to develop strategic, baselined, data modeling processes; ability to accurately determine cause-and-effect relationships. Experience with ML fields, e.g., natural language processing, computer vision, statistical learning theory; Experience in an ML engineer or data scientist role building ML models; Experience writing code in Python, R, Scala, Java, C++ with documentation for reproducibility; Experience handling terabyte size datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL, and working with GPUs to develop models; and.