Senior Data Scientist

Description: Build and own machine learning models for ETA/ATA forecasting and message-based status extraction. Work end-to-end from data pipeline to production deployment and monitoring, using real-world logistics data. Requirements: Strong ML fundamentals in regression, classification, and time-series forecasting. Experience with NLP, production ML, Python, SQL, AWS, and model monitoring tools. Ability to work with noisy data and diagnose performance gaps between offline and live models. Experience mentoring other data scientists and making independent architecture decisions. Benefits: Medical benefits start on the first day of employment. 36 PTO days, 5 recharge days, 2 volunteer days, and wellness stipends.