POSITION SUMMARY: A Data Science leader responsible for developing a cross-market strategy in the application of data science (deep learning, machine learning, Artificial Intelligence) techniques and tools. Position is responsible for representing the Company's big-data, analytics and deep learning initiatives, developing common architectures and design patterns, developing how-to-adopt approaches, developing and implementing a strategy to expand implementation across program and customer portfolio. RESPONSIBILITIES: Position is one of strategy and architecture, as well as implementation. Responsibilities include considerable communications written and oral, constructing the overall system architectures or technical solutions, to include external and internal interface analysis, internal interface definition, and functional requirement allocations. May lead a multidisciplinary team of engineers and scientists responsible for the research and development of technical solutions and architectures in support of program or strategic objectives. Provides guidance to management for current and proposed investments and bid/no-bid decisions. EDUCATION & EXPERIENCE - Education and Clearance Requirements - B.S., M.S. in Engineering Field of Study - Completed PhD or significant progress in PhD program (e.g., completion of coursework but short of approved final dissertation) in Engineering Field of Study - TS/SCI Clearance - Experience - 3+ years required, combined in Commercial and Government - Experienced with development of analytics in relevant market (e.g. cyber security, intelligence, health) - Experienced with Machine Learning at scale - Experienced with practical application of deep learning, linear regression, k-means clustering (vector quantization), Tensor Flow, and/or other machine learning models and implementations. - Experienced with streaming analytics and real-time conversion to actionable intelligence - Experienced with developing strategies in Data Science and able to convey for decision with C-Suite customer and Senior Management - Technology skills must include hands-on experience including Python, Hadoop, Kafka, Hive, and other relevant languages and implementations.