Lead Data Scientist

At MITRE, your passion fuels work that impacts our nation and improves lives. This is where your skills strengthen national security, cybersecurity, health, transportation, and citizen services. We’re a nonprofit engineering, applied research, and advanced technology organization working in the public interest. With objectivity and integrity at our core, we lead federally funded research and development centers for U.S. government agencies – collaborating with industry and academia to deliver integrated, high-impact solutions that advance our nation’s health, security, and prosperity.

Our people tackle the toughest technical challenges, supported by competitive benefits, meaningful career development, and a culture of innovation, collaboration, and technical excellence. Choose MITRE for a career with purpose – and help shape the future.

MITRE’s Data Science and Engineering department is looking for qualified applicants to bring their advanced data science, data engineering, machine learning, artificial intelligence, and applied research skills to bear on solving problems of critical national importance. MITRE’s diverse work program provides opportunities to apply your expertise and creative thinking in challenging domains such as national security, intelligence, transportation, and healthcare. Employees may also participate in MITRE’s internal research and development program, which provides funding for innovative applied research that addresses our sponsors’ hardest problems.

The successful candidate for this position is a hybrid Data Scientist and Data Engineer who combines strong foundations in computer science, mathematics, and software engineering with hands-on experience designing data systems and applying advanced analytics, machine learning, and AI techniques to solve mission problems. This role requires practitioners who can operate across the full data lifecycle from data modeling, processing, and infrastructure engineering to statistical analysis, machine learning, experimentation, and operational deployment.

Our organization values innovation and believes that keeping up with the latest research and technologies is essential.

The candidate should have hands‑on experience in several of the areas specified below, however it is not required that a candidate has experience in all of these areas.

• Machine Learning and Model Evaluation (e.g., supervised, unsupervised, deep learning, reinforcement learning)
• Statistical Analysis and Exploratory Data Analysis (e.g., descriptive statistics, regression, visualization)
• Large Language Models and AI‑Assisted Workflows
• Natural Language Processing (e.g., summarization, classification, entity recognition, topic modeling)
• Anomaly Detection and Predictive Modeling
• Graph Analytics (e.g. centrality, similarity, link prediction)

• Distributed Data Processing and Big Data Architectures (e.g., Spark, Hadoop, Ray, Dask, Kafka)
• Data Pipeline/ETL Development and Orchestration (e.g., Airflow, Dagster, NiFi)
• Batch and Streaming Data Processing
• Data Modeling, Schema Design, and Data Quality Assessment
• Data Governance, Access Controls, and Secure Data Handling
• Cloud‑based Data Platforms and Storage Architectures

• Computer Programming and Databases – Proficiency in Python and SQL required
• Software Engineering Best Practices (e.g., version control, testing, modular design)
• MLOps and Model Operationalization (e.g., model deployment, monitoring, reproducibility, containerization)
• Linux‑based Development Environments, Git, Containers, and Cloud Platforms

• Leads functional teams or complex…