Gormat is seeking a Data Scientist with experience with pattern/trend analysis while leveraging financial and geospatial datasets. Experience with LLM is desired as well as experience in AI/ML development leveraging SIGINT data. Python proficiency is required using skills such as data mining, algorithmic application and heuristics. Automated alert metrics tracking are a plus. You will need the ability to translate complex data into strategic insights, and target knowledge or experience in OCP is a plus. The Level 2 Data Scientist shall possess the following capabilities: Foundations: (Mathematical, Computational, Statistical). Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility). Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations). Ability to make and communicate principal conclusions from data using elements of mathematics, statistics, computer science, and applications-specific knowledge. Ability to use analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique feature and limitations inherent in Customer data holdings. Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data. Effectively communicate complex technical information to non-technical audiences. Pattern/trend analysis experience required while leveraging financial datasets. LLM and NER experience desired. Any AI/ML development leveraging SIGINT data. Python proficiency including data mining, algorithmic application, and heuristics. Automated alert metrics tracking a plus. Ability to translate complex data into strategic insights. Target knowledge or experience in OCP a plus.
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Job Type
Full-time
Career Level
Mid Level