Lead Data Scientist at The MITRE Corporation

New Bedford, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

15 Sep, 26

Salary

232800.0

Posted On

17 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Engineering, Artificial Intelligence, Python, SQL, Deep Learning, Natural Language Processing, Big Data Architectures, MLOps, Statistical Analysis, Data Modeling, Cloud Platforms, ETL Development, Graph Analytics, Anomaly Detection, Software Engineering

Industry

Research Services

Description

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 Controls, 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: Leads functional teams or complex projects with moderate resource requirements, risks, or complexities; Develops strategies and objectives and leads others to execute them. Works independently, with guidance needed only in highly complex situations. Identifies and leads others to solve complex problems; Uses sophisticated analytical thought to exercise judgement and identify innovative applications; May develop and recommend solutions to novel or atypical problems within the Data Science and Data Engineering disciplines. Applies extensive in-depth conceptual, practical, and technical knowledge within the Data Science and Data Engineering disciplines and transfers that knowledge to others. Communicates complex concepts clearly and simply and persuades others to adopt a different point of view. Basic Qualifications: Bachelor’s degree in Computer Science, Applied Mathematics, Statistics, Data Science, or related field with 8 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 very large datasets. Computer programming skills (e.g., Python, R, C/C++, Java, Scala, Julia, Rust, MATLAB). The ability to obtain and maintain a DoD Top Secret clearance within 12 months of hire. Per the U.S. Government’s eligibility requirements, you must be a U.S Citizen to be considered for a security clearance. This position requires a minimum of 50% hybrid on-site Preferred Qualifications: Master’s degree in Computer Science, Applied Mathematics, Statistics, Data Science, or related field with 6 years of relevant experience; PhD in Computer Science, Applied Mathematics, Statistics, Data Science, or related field with 3 years of relevant experience. Active DoD Top Secret Clearance. This requisition requires the candidate to have a minimum of the following clearance(s): None This requisition requires the hired candidate to have or obtain, within one year from the date of hire, the following clearance(s): None Salary compensation range and midpoint: $155,200 - $194,000 - $232,800 Annual Work Location Type: Hybrid It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Commitment to Non-Discrimination All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local or international law. MITRE intends to maintain a website that is fully accessible to all individuals. If you are unable to search or apply for jobs and would like to request a reasonable accommodation for any part of MITRE’s employment process, please email recruitinghelp@mitre.org for general support and collegerecruiting@mitre.org for intern positions. This service is for individuals requiring reasonable accommodation requests. Please note that vendor solicitations will not receive a reply. Benefits information may be found here. Copyright © 1997-2026, The MITRE Corporation. All rights reserved. MITRE is a registered trademark of The MITRE Corporation. Material on this site may be copied and distributed with permission only.

Responsibilities

Lead functional teams in designing data systems and applying advanced analytics and AI to solve critical national security and healthcare problems. Manage the full data lifecycle from infrastructure engineering and data modeling to operational deployment and MLOps.