The data our devices generate is rich, complex, and full of untapped potential. We're looking for someone who can take that raw time-series data, design algorithms that make sense of it, and see them through from experiment to deployment all on a product that people actually wear. * Design and own the full pipeline, from data collection and preprocessing to model conception and training, quantitative evaluation, and deployment * Develop and iterate on algorithms for real-world time-series sensor data, including eye-tracking and physiological signals * Build robust data collection strategies that feed high-quality training sets * Apply statistical modelling and machine learning to infer mental states from noisy, real-world data * Strong background in machine learning, data science, statistics, applied mathematics, physics, or a related field
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