n Data Scientists

• Bachelor’s Degree in areas such as Computer Science, Mathematics, Statistics, Artificial Intelligence/Machine Learning, Data Science, and Operations Research and 10 years of relevant experience.\n \n

• An Associate’s degree plus 12 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position.\n
• A degree in other technical fields if you have a coursework concentrating in advanced mathematics, probability and statistics, artificial intelligence/machine learning, computer science, and/or data mining.\n

• A broader range of degrees will be considered if accompanied by certificate in areas such as Data Science and AI/ML.\n \n

• Skill in at least one high-level language such as Python and at least one language such as C/C++ and experience developing data visualization using Tableau, Power BI, or Python libraries.\n
• Ability to translate complex data into strategic insights and automated analytics workflow development and effectively communicate complex technical information to non-technical audiences and collaborate effectively.\n
• Experience in Intelligence or cyber operations and analysis with target knowledge or experience is a plus.\n

nLeidos has new and exciting opportunities for experienced a\n Data Scientists in our \nIntelligence Sector, Cyber & Analytics Business Area (CABA). The work focuses on applying your AI/ML experience to assess large datasets to support development and improvement of CNO Community capabilities with analytics and tools for CNE, Malware Analysis, and sensor improvement. You will have the opportunity to apply your knowledge of data modeling, large language models (LLM), and qualitative and quantitative techniques to normalize, analyze, and visualize RF, PERFORMA, and other SIGINT data in a large-scale data processing environment using technologies such as Spark, cloud data platforms, Python, and SQL.\n \n \nWhat will you do in this role?\n \n \n

• Devise strategies for extracting meaning and value from large datasets and answer analytic questions into technical requirements providing principled conclusions from the data using elements of mathematics, statistics, computer science, AI/ML, and domain specific knowledge.\n
• Characterize, explore, and assess large datasets in various states of organization, cleanliness, and structure inherent in Intelligence data holdings for mission needs.\n
• Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting intelligence collection, processing, storage and analytic capabilities and limitations.\n