Senior ML/AI Researcher II - ML and AI modeling

Candidates must possess a BA/BTech in Statistics, Data Science, Computer Science, or a related field, along with 6+ years of experience in statistical analysis and machine learning, including ML modeling, hyperparameter tuning, feature engineering, and model validation. A strong understanding of causal inference and treatment effects estimation is required, complemented by 3-5 years of experience in selecting, implementing, and optimizing ML tools and frameworks for large-scale projects. Proficiency in Python (2+ years) and experience with deep learning and LLMs (1+ years) are essential, as is experience with large-scale distributed systems and statistical software like Spark (1+ years). The role also requires experience addressing challenges with incomplete, unrepresentative, and mislabeled data, and demonstrated contributions to the field through publications, patents, or successful large-scale implementations. Preferred qualifications include a Master's or PhD in a quantitative discipline, background in epidemiology, working knowledge of public health and health-tech systems, and proficiency in communicating complex analysis to diverse audiences.