Pay
In line with similar jobs
$120K–$150K against $127K–$190K, the middle half of what similar US postings state.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Fort Meade, MD
Actively hiring, first seen by us 7 days agoSalary 120,000 – 150,000 USD per year Our Core ValuesRead the full posting
Top Secret, Must Have Clearance to Start
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, Must Have Clearance to Start
3+ years of experience in data engineering or software engineering, with demonstrated experience in designing and managing complex data pipelines
Typically has a Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field
Experience with data visualization and storytelling using tools such as Palantir's MSS Workshop and Slate applications
4+ years of experience in applied data science, Palantir Foundry development, 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).
Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
Education and Background Typically has a Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (masters degree preferred)., and 3+ years of experience in data engineering or software engineering, with demonstrated experience in designing and managing complex data pipelines., or equivalent relevant work experience; e.g., each year of work experience may be substituted for each year of education required. Years of Experience
At Agile Defense we know that action defines the outcome and new challenges require new solutions.
In the employer’s words · Read in context
Actively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
In line with similar jobs
$120K–$150K against $127K–$190K, the middle half of what similar US postings state.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Day 7
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- 4+ years of experience in applied data science, Palantir Foundry development, 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).
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). - 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). - Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
120,000 – 150,000 USD per year
Regular
Selected passages from the saved posting. Check the full description for conditions and exceptions.
Salary 120,000 – 150,000 USD per year Our Core Values
Fort Meade, MD
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.