Data Scientist Security Clearance

Position: Data Scientist with Security Clearance
Why choose between doing meaningful work and having a fulfilling life? At MITRE, you can have both. That's because MITRE people are committed to tackling our nation's toughest challenges-and we're committed to the long-term well-being of our employees. MITRE is different from most technology companies. We are a not-for-profit corporation chartered to work for the public interest, with no commercial conflicts to influence what we do.

The R&D centers we operate for the government create lasting impact in fields as diverse as cybersecurity, healthcare, aviation, defense, and enterprise transformation. We're making a difference every day-working for a safer, healthier, and more secure nation and world. Our workplace reflects our values. We offer competitive benefits, exceptional professional development opportunities for career growth, and a culture of innovation that embraces adaptability, collaboration, technical excellence, and people in partnership.

If this sounds like the choice you want to make, then choose MITRE - and make a difference with us. 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.

Roles & Responsibilities :
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. Advanced Data Analytics and Artificial Intelligence
* 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)
Data Engineering
* 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 Control, and Secure Data Handling

* Cloud-based Data Platforms and Storage Architectures
Software Development and MLOps
* 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 Expectations for this position are as follows:
* As an individual contributor, requires a moderate level of instruction, guidance, and direction from more senior staff and is progressing toward working independently.

* Provides informal guidance to new or junior team members.

* Identifies and solves routine problems;
Analyzes possible solutions using technical experience and established precedents within the Data Science and Data Engineering disciplines.

* Leverages intermediate level of knowledge of Data Science and Data Engineering and applies it to individual and team work products.

* Communicates complex information, both written and verbal, to technical and non-technical audiences in routine situations.

Basic Qualifications:

* Bachelor's degree in Computer Science, Applied Mathematics, Statistics, Data Science, or related field with 2 years of relevant experience.

* Hands-on proficiency with advanced Data Science techniques, including Machine Learning (e.g., supervised, unsupervised, deep learning, reinforcement learning), anomaly detection, statistical analysis, and/or analysis of…