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Data Scientist

Pay
Pay not listedSimilar roles state $118K–$194K
Work setting
Not stated
Employment
Not stated

Before you apply

Work authorization
Citizens onlyTop Secret with the ability to obtain an SCI, Must Have Clearance to Start

What you’ll work on

Full posting
  • 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

From the employer’s posting
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

What you’ll bring

All qualifications

Core experience

  • Top Secret clearance with ability to obtain SCI; must have clearance to start
  • 4+ years in applied data science, ML engineering, or data pipeline development
  • Proficient in Python, SQL, and distributed data frameworks such as Spark or PySpark
  • Bachelor's degree plus 3 years recent specialized experience (or equivalent alternatives)

Preferred 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.
Qualification wording
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 & alternatives
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

About Agile-Defense

At Agile Defense we know that action defines the outcome and new challenges require new solutions.

In the employer’s words · Read in context

Apply at Agile-Defense

Posting record

Report an error

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.

Status in our records
Live
First seen by us
May 8, 2026181 days ago
Recorded sightings
197
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$194K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,768 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

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 10,418 similar postings that came down, and 29 of Agile-Defense’s. Coming down is not always a hire.

Agile-Defense is hiring

28 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

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.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • MLflow
  • Spark
  • Tableau
  • Matplotlib
  • Plotly
  • PySpark
  • scikit-learn
  • TensorFlow
  • XGBoost
Where the posting names them
- 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.

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Has Agile-Defense posted this job before?

Yes. We’ve followed 2 other Data Scientist jobs there since March 2026. One came down after 40 days. One is still up.

  1. Macdill AfbCame down after 40 days, first seen Mar 21
  2. This jobUp 182 days so far, first seen May 8
  3. WashingtonStill up after 164 days, first seen May 26

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,818.
August 17Last week

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.

About the role

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.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

About Agile Defense
 
At Agile Defense we know that action defines the outcome and new challenges require new solutions. That’s why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next.
 
Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility—leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation’s vital interests.

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

 

Job Descripton

    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.

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

  • 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

  • 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.

Working Conditions

    Requires work onsite in a SCIF
Our Core Values
 
Employees of Agile Defense are our number one priority, and the importance we place on our culture here is fundamental. Our culture is alive and evolving, but it always stays true to its roots. Here, you are valued as a family member, and we believe that we can accomplish great things together. Agile Defense has been highly successful in the past few years due to our employees and the culture we create together. 
 
What makes us Agile? We call it the 6Hs, the values that define our culture and guide everything we do. Together, these values infuse vibrancy, integrity, and a tireless work ethic into advancing the most important national security and critical civilian missions. It's how we show up every day. It's who we are.
 
  • Happy - Be Infectious. Happiness multiplies and creates a positive and connected environment where motivation and satisfaction have an outsized effect on everything we do.
  • Helpful - Be Supportive. Being helpful is the foundation of teamwork, resulting in a supportive atmosphere where collaboration flourishes, and collective success is celebrated.
  • Honest - Be Trustworthy. Honesty serves as our compass, ensuring transparent communication and ethical conduct, essential to who we are and the complex domains we support.
  • Humble - Be Grounded. Success is not achieved alone, humility ensures a culture of mutual respect, encouraging open communication, and a willingness to learn from one another and take on any task.
  • Hungry - Be Eager. Our hunger for excellence drives an insatiable appetite for innovation and continuous improvement, propelling us forward in the face of new and unprecedented challenges.
  • Hustle - Be Driven. Hustle is reflected in our relentless work ethic, where we are each committed to going above and beyond to advance the mission and achieve success.
 
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

Employment type

Regular

Source details

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Pay

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Location & working pattern

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.
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