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 determine information values, trends, patterns, and relationships-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.

• Accurately determine feasibility of aggregating, transporting, storing, and safeguarding the data.
• Develop and deploy Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and Computer Vision algorithms and models for signal processing, geospatial analytics, object detection, anomaly detection, and to enable prediction.
• Analyze data to identify insights that can be gleaned from the data by determining information values, trends, patterns, and relationships within the data.
• 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 modern development stacks including Python, Java script Application Programming Interface (API), Docker, Visual Studio (VS) Code, Jupyter, Gitlab, Git, and Continuous Integration/Continuous Delivery (CI/CD) pipelines.
• Collaborate with analysts, engineers, and mission leads to prototype and iterate on solutions rapidly.

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.
• Strong mathematics background in Statistics, Graph Theory, Probability, or Calculus to develop and test algorithms and models .
• 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, Python, Java script Application Programming Interface (API), Docker, Visual Studio (VS) Code, Jupyter, Gitlab, Git, 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.
• Background in Agile environments with rapid prototyping capabilities.