This role pays more than
61%
of similar roles. Most pay
$126,800–$191,250
— the shaded band above.
At the midpoint, this role pays about
$162k
versus about
$159k
for comparable roles.
Based on 240 similar postings.
Employer
About Booz Allen Hamilton
Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting
Booz Allen Hamilton currently has
690 open roles
on FindRole.
Listed pay typically runs
$86,800–$198,000
across 681 roles with salary data.
Join our dynamic team as an Applied Data Scientist where you will design, develop, and deploy machine learning and AI-driven solutions to real-world problems. You’ll collaborate closely with clients to translate their mission needs into technical solutions by building robust data pipelines, training models, and deploying them in production environments. Your daily tasks include applying statistical methods, machine learning techniques, and software engineering practices to deliver end-to-end operational systems that provide measurable impact. Ideal candidates have 5+ years of experience in developing ML/AI algorithms, deploying solutions into production, designing full ML pipelines, and writing high-quality Python code. Experience with large-scale data processing, modern software engineering tools like Git and CI/CD, and working in Linux or cloud environments is essential. Additional skills such as deep learning, reinforcement learning, containerization, and integration of AI capabilities into larger systems are highly valued.
Python
R
SQL
data visualization
machine learning algorithms
supervised machine learning
unsupervised machine learning
structured datasets
unstructured datasets
data cleansing
data analytics
inferential statistics
system integration
research design principles
analytic methods
methodological tools
psychometric theory
Item Response Theory
Factor Analysis
data strategy
data governance