Lead Data Scientist

The MITRE Corporation•New Bedford, MA

4d•$155,200 - $232,800•Hybrid

About The Position

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. Department Summary: 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.

Requirements

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).
Proficiency in Python and SQL required.
Must be eligible to obtain and maintain a Top Secret U.S Government issued Security Clearance.
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 3 days per week on-site.

Nice To Haves

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.
Experience with distributed data processing and big data architectures (e.g., Spark, Hadoop, Ray, Dask, Kafka).
Experience with data pipeline/ETL development and orchestration (e.g., Airflow, Dagster, NiFi).
Experience with batch and streaming data processing.
Experience with data modeling, schema design, and data quality assessment.
Experience with data governance, access controls, and secure data handling.
Experience with cloud-based data platforms and storage architectures.
Experience with software engineering best practices (e.g., version control, testing, modular design).
Experience with MLOps and model operationalization (e.g., model deployment, monitoring, reproducibility, containerization).
Experience with Linux-based development environments, Git, containers, and cloud platforms.
Experience with Large Language Models and AI-Assisted Workflows.
Experience with Natural Language Processing (e.g., summarization, classification, entity recognition, topic modeling).
Experience with Graph Analytics (e.g. centrality, similarity, link prediction).

Responsibilities

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 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.
Design data systems.
Apply advanced analytics, machine learning, and AI techniques to solve mission problems.
Operate across the full data lifecycle from data modeling, processing, and infrastructure engineering to statistical analysis, machine learning, experimentation, and operational deployment.
Keep up with the latest research and technologies.