Job ID: 2612311
Location: Upper Marlboro, MD, United States
Date Posted: Jun 15, 2026
Category: Information Technology
Subcategory: Data Scientist
Schedule: Full-Time
Shift: Day Job
Travel: Yes - 10% of the time
Minimum Clearance Required: None
Clearance Level Must Be Able to Obtain: Public Trust
Potential for Remote Work: Hybrid
Benefits:

Description

SAIC is looking for a Data Scientist Associate to help the Identity and Data Sciences Laboratory (IDSL) which is tasked with identifying state-of-the-art technologies including facial recognition and AI, evaluating performance, and examining their applicability to existing or emerging customer use cases. The IDSL has a cutting-edge infrastructure consisting of both on-prem distributed computing clusters and cloud based analytic environments, which we use for gathering and processing multi-modal data in real-time from large-scale experiments conducted at our test facility (Maryland Test Facility; http://mdtf.org), in field locations, as well as from external data sources.

Hybrid - 3 Days in Office / 2 Days Remote

What You Will Be Doing:

• Contribute to data acquisition, management, and processing tasks, working with senior data scientists, software engineers and evaluation designers to build efficient data pipelines
• Access available infrastructure, and to develop analytic products tailored to mission user requirements
• Work with senior team members to organize, clean, migrate and process datasets with advanced computer vision algorithms
• Testing different LLMs

Qualifications

Requirements:

• A bachelor’s degree in computer science, data science, or a comparative quantitative science or scheduled to obtain one by spring or summer 2026
• Ability to obtain and maintain a public trust requiring US Citizenship
• Proficient in programming a must (Python, C++, Golang, Java, etc.)
• Ability to build out data pipelines as this will be the main function of role
• Desire to learn GoLang
• Familiar with machine learning, data mining, and/or statistics (R, Python, etc.)
• Familiar with source control (e.g., Git)
• Familiar with common data formats (JSON, Parquet, XML, etc.)
• Familiar with database technologies (SQL, NoSQL)
• Strong communication skills, with the ability to present findings and recommendations to both technical and non-technical audience

Desired Skills:

• Prior experience related to data engineering, data science, data architecture, and databases
• Understanding of scaling and performance of distributed/cloud systems (AWS)
• Understanding of data science concepts, AI/ML, automation, and scripting
• Experience with techniques and platforms to manage, manipulate, and draw insight from large datasets (Spark, Hadoop, Databricks, etc.)