Job Location : New York,NY, USA
Join to apply for the Core AI Principal Scientist - Time Series role at Keystone AI
Core AI Principal Scientist - Time Series2 days ago Be among the first 25 applicants
Join to apply for the Core AI Principal Scientist - Time Series role at Keystone AI
Principal Applied Scientist – Time Series ForecastingCompany BackgroundKeystone.AI is a premier artificial intelligence, economics, and technology firm providing AI-driven services to large companies, law firms, and government agencies. The firm builds and deploys enterprise AI solutions at-scale that automate and optimize operational and commercial decision-making. We are all connected by one mission: bringing transformative ideas to life on behalf of our clients. Keystone's Core AI group employs the world's best AI/ML science and technology practitioners with unparalleled experience implementing highly complex, massive-scale algorithms and models to help companies make better decisions across manufacturing, supply chain management, sales, and marketing.Position OverviewWe are seeking a Principal Applied Scientist who will serve as a thought leader and drive the development of our foundational forecasting capabilities - Keystone's flagship product for advanced time series forecasting and intelligent inventory management. Our team builds sophisticated forecasting solutions deployed across diverse industries, helping clients transform critical business processes, reduce waste, and modernize operations through data-driven insights and predictive modeling.In this role, you will lead other scientists and ML engineers, shaping the design, development, and deployment of robust forecasting models leveraging fundamental economic and structural time series techniques. You will use your extensive experience in econometric modeling, statistical forecasting methods, and applied time series analysis to produce innovative, industry-leading solutions that optimize supply chain and operational workflows.If you are passionate about pushing the boundaries of forecasting methods, mentoring high-performing teams, and collaborating closely with business and technical stakeholders to deliver practical, impactful solutions, we invite you to apply. While deep expertise in deep learning techniques is not required, familiarity or exposure to such methods for time series forecasting is a plus.What You'll Do
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