Data Scientist

Anonymous Employer
Washington, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Washington, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Azure
Cloud Computing Security
Continuous Delivery
Data as a Services
Data Validation
Data Systems
Data Visualization
Distributed Data Store
Python
Machine Learning
TensorFlow
Software Engineering
SQL Databases
Tableau
Cloud Platform System
Feature Engineering
Spark
Matplotlib
PySpark
Scikit Learn
XGBoost
Plotly
Machine Learning Operations
Api Design
Data Pipelines
Databricks

Job description

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.

Requirements

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., 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.

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