Data Scientist - TSSCI w​/Poly

Job Description

Core Responsibilities

• Develop, train, and optimize machine learning algorithms for mission use cases
• Build predictive analytics models using intelligence data from multiple sources
• Integrate disparate intel datasets (structured, unstructured, geospatial) into unified analytical pipelines
• Use Oracle Machine Learning (OML) as the primary modeling environment
• Design and implement AI enhanced data pipelines, including metadata extraction, enrichment, lineage, and cataloging
• Apply LLM based techniques (RAG, MCP) to augment predictive workflows
• Build and maintain SQL, Python, and R based analytical scripts and services
• Collaborate with AI engineers to integrate models into mission applications and dashboards
• Work with geospatial data types (rasters, vectors) for spatial ML and predictive modeling
• Develop reproducible notebooks, AutoML workflows, and model evaluation frameworks

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations.

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Skills and Requirements

Required Skills

• Strong foundation in ML algorithms, predictive modeling, and statistical learning
• Experience integrating and preparing intelligence data for analysis
• Hands on experience with Oracle Machine Learning (OML)
• Proficiency in SQL, Python, R
• Experience with geospatial data (rasters, vectors)
• Ability to build and maintain data pipelines for ingestion, normalization, enrichment, and orchestration
• Familiarity with LLM augmented workflows (RAG, MCP)
• Ability to work with mission stakeholders to translate data into actionable predictions