Pay
$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Falls Church, VA
Open 6 months, first seen by us 181 days agoTop Secret with the ability to obtain an SCI, Must Have Clearance to Start
Help design and deploy data pipelines and pre-processing workflows
Build feature engineering strategies and machine learning services
Turn raw data into insights and decision-support tools with mission stakeholders
You will help shape and deploy data pipelines, pre-processing workflows, feature engineering strategies, and machine learning services within secure, containerized environments.
feature engineering strategies, and machine learning services within secure, containerized environments
transform raw data into meaningful insights and decision-support tools
Top Secret with the ability to obtain an SCI, Must Have Clearance to Start
4+ years of experience in applied data science, machine learning engineering, or data pipeline development.
Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark
A bachelor's degree plus 3 years of recent specialized experience
Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).
Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
Strong understanding of data validation, model testing, and performance evaluation techniques.
Experience with data visualization and storytelling using tools such as Tableau, Plotly, or Matplotlib.
Education and Background A bachelor's degree plus 3 years of recent specialized experience, OR, an associate's degree plus 7 years of recent specialized experience, OR, a major certification plus 7 years of recent specialized experience, OR, 11 years of recent specialized experience Required Skills
At Agile Defense we know that action defines the outcome and new challenges require new solutions.
In the employer’s words · Read in context
Open 6 monthsWe first saw this posting 181 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Day 181
Up longer than most. Similar jobs usually come down between day 7 and day 56.
Well past Agile-Defense’s usual: its jobs come down by about day 30.
From 10,312 similar postings that came down, and 29 of Agile-Defense’s. Coming down is not always a hire.
28 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 4+ years of experience in applied data science, machine learning engineering, or data pipeline development. - Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark Preferred Skills
You will help shape and deploy data pipelines, pre-processing workflows, feature engineering strategies, and machine learning services within secure, containerized environments. The ideal candidate brings a hybrid of statistical modeling fluency and hands-on software engineering expertise. You will collaborate closely with product managers, full-stack developers, platform engineers, and mission stakeholders to transform raw data into meaningful insights and decision-support tools. This role requires strong technical communication skills, a collaborative mindset, and experience working in agile environments that value reproducibility, testing, and continuous delivery. Familiarity with cloud-based data platforms such as Databricks, Palantir, or AWS-native data services is highly preferred. Education and Background
- Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow). - Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry). - Strong understanding of data validation, model testing, and performance evaluation techniques.
Preferred Skills - Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow). - Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
- Strong understanding of data validation, model testing, and performance evaluation techniques. - Experience with data visualization and storytelling using tools such as Tableau, Plotly, or Matplotlib. - Excellent technical communication skills, with the ability to explain complex concepts to non-technical audiences.
Complete your application on jobs.lever.co. The employer’s form will show what is required.
Already applied? Track this application
Yes. We’ve followed 2 other Data Scientist jobs there since March 2026. One came down after 40 days. One is still up.
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Requisition #: 1590
Job Title: Data Scientist
Location: In Person: Falls Church, VA | Ft. Meade, MD | Stuttgart, Baden-Württemberg, Germany | Tampa, FL | Honolulu (Camp H.M. Smith), HI | Colorado Springs, CO | Doral (Miami area), FL | Omaha (Offutt Air Force Base), NE | Scott Air Force Base, IL
Clearance Level: Top Secret with the ability to obtain an SCI, Must Have Clearance to Start
Regular
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Falls Church, VA
Agile Defense is seeking a Data Scientist / Engineer to support the design, development, and operational deployment of scalable, AI-enabled data solutions within the Department of Defense’s CDAO ADA IR program. This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and engineering practices into mission-critical environments at Combatant Commands. You will help shape and deploy data pipelines, pre-processing workflows, feature engineering strategies, and machine learning services within secure, containerized environments. The ideal candidate brings a hybrid of statistical modeling fluency and hands-on software engineering expertise. You will collaborate closely with product managers, full-stack developers, platform engineers, and mission stakeholders to transform raw data into meaningful insights and decision-support tools. This role requires strong technical communication skills, a collaborative mindset, and experience working in agile environments that value reproducibility, testing, and continuous delivery. Familiarity with cloud-based data platforms such as Databricks, Palantir, or AWS-native data services is highly preferred.
No clear work-authorization passage found. Eligibility is unconfirmed.