Responsibilities
Design and implement advanced algorithms to merge and interpret diverse data sources collected from various sensing systems.
Evaluate and extract meaningful information from complex inputs such as radar, electro-optical/infrared imagery, and radio-frequency signals to enhance operational awareness.
Simulate and predict system performance under changing conditions using probabilistic and statistical modeling techniques.
Work closely with experts from engineering, analytics, and mission-focused teams to create prototypes and transition them into field-ready solutions.
Apply data-driven methods to uncover, classify, and monitor sophisticated threats and hostile strategies.
Convey analytical results in clear, actionable formats for audiences ranging from technical specialists to decision-makers.
Monitor and integrate emerging developments in data science, artificial intelligence, machine learning, and sensor exploitation technologies into ongoing work.
Requirements
Degree in a quantitative discipline such as applied mathematics, computational science, physics, aerospace engineering, or a similar technical field. Equivalent industry experience may substitute for formal education at the graduate level with 4-6 years of experience.
Proven track record applying multi-sensor data integration methods and estimation frameworks, including approaches for navigation, mapping, and target tracking.
Solid grasp of the principles behind various sensing modalities, such as radar, LiDAR, and optical imaging technologies.
Background in handling live data distribution frameworks or event-driven architectures.
Experience devising and implementing models to forecast, classify, and detect evolving security or defense-related risks.
Proficient in one or more technical programming environments (e.g., Python, C++, MATLAB) for algorithm development, simulation, and data processing.
Desired Attributes
History of contributing to research or prototype development within defense, aerospace, or intelligence programs.
Familiarity with fielded military technologies, autonomous platforms, or surveillance and reconnaissance systems.
Understanding of machine learning applications for analyzing sensor or signal datasets.
Experience managing spatiotemporal datasets or integrating geospatial analytics into operational workflows.
