Additional for Decision Scientist III: Ability to design systems across batch, streaming, and real-time processing; ability to evaluate cutting-edge ML research and frameworks; familiarity with semi-supervised, reinforcement, transfer, and graph-based learning; ability to simplify and improve the full ML model life cycle; strong facilitation and consensus-building skills; proven ability to influence others; ability to build ML pipelines through full ML cycles; ability to effectively lead teams without direct supervisory responsibility. Familiarity with mixed methods research, with experience in at least two of the following: advanced analytics (statistics, simulation, optimization, time series, longitudinal studies, life event modeling); data mining, NLP, machine learning (regression, clustering, neural networks, kernel methods, dimensionality reduction, ensemble methods, decision trees) and deep learning (CNN, LSTM, GAN); building solutions with tools for data mining, statistics, analysis and scripting (e.g., Python).