Data Scientist

• Develop and execute machine learning and data science experiments in natural language processing, computer vision, time series analysis, reinforcement learning, and related domains
• Test, experiment with, and deploy ML-powered systems
• Evaluate technologies and data science models for scalable and resilient mission-critical applications
• Collaborate with teams of various sizes to deliver features and products
• Present written and verbal results to customer stakeholders
• Reinforce an environment of learning and progress with team members and others

• Analyze large, complex, and diverse datasets to establish baselines, identify patterns and trends, develop indicators, and support operational decision-making
• Develop and automate analytic workflows using Python, R, and related data science tools
• Apply statistical and quantitative techniques including regression, hypothesis testing, sampling, longitudinal analysis, network analysis, modeling, and reliability/validity assessment
• Develop prototypes, scripts, and analytical tools for data collection, processing, integration, visualization, and synthesis
• Apply AI/ML and Natural Language Processing (NLP) techniques to structured and unstructured data
• Conduct qualitative and mixed-methods analysis including thematic coding, classification, sentiment analysis, and NLP-assisted analysis
• Develop dashboards, visualizations, and analytical products for operational leaders and mission stakeholders
• Integrate analytical findings with intelligence and operational reporting to establish baselines, measure effects, identify emerging trends, and assess OIE/IW activities
• Manage and optimize analytical datasets, databases, metadata, and longitudinal data
• Apply geospatial analysis and visualization techniques
• Leverage social media and publicly available data using automated collection, analytics, AI/ML, and NLP techniques
• Support research and assessment design through analytical methodologies, data collection strategies, assessment criteria, and measures of performance and effectiveness
• Collaborate with multidisciplinary intelligence, operations, technology, and research teams to translate mission requirements into data-driven analytical solutions