Data Scientist

FRDA is looking for a Data Scientist to join a multidisciplinary team developing analytic capabilities, capturing workflows, designing predictive models and developing business processes for real-world mission challenges. This role supports defense, intelligence, and federal clients by building machine learning models, data pipelines, and APIs to derive insights from complex data-particularly in signal, image, and geospatial domains-and working with structured and unstructured data to generate insights for operations or strategic decision-making., * Design, build, and maintain robust data pipelines for structured and unstructured data.

• Develop and deploy models for signal processing, geospatial analytics, object detection, and anomaly detection.
• Implement analytics as RESTful services for use in tactical or operational environments.
• Clean, process, and format raw data into actionable, mission-ready outputs.
• Support edge-computing constraints and adapt models to operate in austere or bandwidth-constrained settings.
• Work within a modern development stack including Python, Git, Docker, and FastAPI.
• Collaborate with analysts, engineers, and mission leads to prototype and iterate on solutions rapidly.

Do you have experience in Scikit-learn?, Do you have a Master’s degree?, This role is ideal for someone with a strong interest in high impact, mission-focused work in a fast-paced DOD environment., * Active TS/SCI clearance.

• Bachelor’s degree in Data Science, Computer Science, Engineering, or related field.
• A minimum of four (4) years of experience in data science, machine learning, or analytics in a production or research setting.
• Proficiency with Python (NumPy, Pandas, Scikit-learn, OpenCV), SQL, R, and Git.
• Experience in building end-to-end analytic solutions-from data ingestion to deployment-and data visualization tools.
• Exposure to signal processing, computer vision, or geospatial analytics projects., * Master’s degree or certifications in data engineering, machine learning, or related areas.
• Familiarity with FastAPI, Docker, cloud services (e.g. AWS, Azure), and REST APIs.
• Software engineering and/or application development to support automating processes, dashboards, and workflows.
• Experience supporting national security, defense, or intelligence community use cases.
• Exposure to edge-AI environments or low-latency ML deployments.