Data Scientist with Java
Job details
- Pay
- $200,001 – $240,000 a year
- Employment
- Full-time
- Education
- Bachelor's degree
- Posted
- Oct 11, 2026
- Last confirmed open
- Oct 11, 2026
About this role
Job ID 2617032
Location
McLean, VA, US
Date Posted
2026-09-18
Category
Information Technology
Subcategory
Data Scientist
Schedule
Full-Time
Shift
Day Job
Travel
No
Minimum Clearance Required
TS.SCI_wPoly
Clearance Level Must Be Able to Obtain
None
Potential for Remote Work
ORA_ON_SITE
Description
SAIC is seeking a
Data Scientist
to join our team to provide support specializing in natural language(NLP) processing and associated data preparation. The ideal candidate will have an extensive background in Java and Python.
This position in in Mclean, VA and requires a TS/SCI with polygraph.
Key Responsibilities
- Assess, maintain and rewrite legacy Java applications.
- Refactor and extend existing back end systems.
- Write clean, scalable and efficient code to support business applications.
- Leverage dominant frameworks to build backend applications and REST API's.
- Write and optimize queries across relational and non-relations databases.
- Utilize test libraries, such as JUnit and Mockito to ensure application stability.
Qualifications
- Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience ; PhD or JD and four (4) years or more experience.
- Demonstrated experience with Core Java Object-oriented programming (OOP) concepts, multithreading, and memory management (JVM).
- Demonstrated experience with Spring and Spring Data JPA.
- Demonstrated experience with tools and build systems such as Eclipse, Maven, Gradle, Git, and Jenkins.
- Demonstrated experience with Oracle, Apache Tomcat, AWS Cloud Framework and Linux.
- TS/SCI with polygraph.
Desired Skills
- Demonstrated experience with Spring Boot and REST API Java implementations to support web applications.
Target salary range $200,001 - $240,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.