Pay
Lower than most similar jobs
$130K–$155K against $166K–$240K, the middle half of what similar US postings state.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Data Scientist
Reads like a ML Engineer role: putting models into production.
Washington, D.C.
Open 5 months, first seen by us 161 days ago- Pay
USD 130,000–155,000/year — pay source
Salary 130,000 – 155,000 USD per year Our Core Values
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
Before you apply
- Work authorization
- Citizens only
Top Secret with the ability to obtain an SCI, Must Have Clearance to Start
What you’ll work on
Full postingDesign and deploy data pipelines and pre-processing workflows
Develop feature engineering strategies and machine learning services
Turn raw data into insights and decision-support tools for 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 qualificationsCore experience
- 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).
- Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).
Preferred experience
- 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
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).
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 Years of Experience
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
Posting record
Report an errorOpen 5 monthsWe first saw this posting 161 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 26, 2026161 days ago
- Recorded sightings
- 166
- Last seen by us
- Nov 4, 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
Time since we first saw it
Day 161
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,301 similar postings that came down. Coming down is not always a hire.
Agile-Defense is hiring
29 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
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). - Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).
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
Preferred Skills - 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.
- Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark). - Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow). Preferred Skills
- 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.
Your next step
Complete your application on jobs.lever.co. The employer’s form will show what is required.
Applying through Lever
- No account needed: one form, and Lever reads your resume into the profile recruiters search.
Already applied? Track this application
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.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
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 #: 1627
Job Title: Data Scientist
Location: Washington, D.C.
Clearance Level: Top Secret with the ability to obtain an SCI, Must Have Clearance to Start
Job Description
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
Years of Experience
Depends on educational background and years of work 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).
- Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).
Preferred Skills
- 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
- Onsite in a SCIF in the Pentagon.
In addition, Agile Defense invests in its employees beyond just compensation. Agile’s benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, short-term and long-term Disability, Retirement and Learning and Development opportunities as well as other optional benefit elections.
Salary
130,000 – 155,000 USD per year
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
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Salary 130,000 – 155,000 USD per year Our Core Values
- Location & working pattern
Washington, D.C.
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.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.