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Data Scientist; Entry Level - SEAL Onsite

Job in Smyrna, Cobb County, Georgia, 30081, USA
Listing for: Georgia Tech Research Institute
Full Time position
Listed on 2026-06-06
Job specializations:
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer, Data Analyst, Artificial Intelligence
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Position: Data Scientist (Entry Level) - SEAL - Open Rank (Onsite)

Overview

The Georgia Tech Research Institute (GTRI) is the nonprofit, applied research division of the Georgia Institute of Technology (Georgia Tech).Founded in 1934 as the Engineering Experiment Station, GTRI has grown to more than 2,900 employees, supporting eight laboratories in over 20 locations around the country and performing more than $940 million of problem-solving research annually for government and industry.

GTRI's renowned researchers combine science, engineering, economics, policy, and technical expertise to solve complex problems for the U.S. federal government, state, and industry.

Location

Smyrna, GA (Metro Atlanta)

Project/Unit Description

The Command, Control, and Communications Division (C3D) within the Sensors and Electromagnetic Applications Laboratory (SEAL) is looking for a Data Scientist to work along side of a team of multidisciplinary researchers focused on artificial intelligence (AI) and machine learning (ML) C3 capabilities for Battle Management (BM) Decision Superiority line-of-effort. C3D delivers robust communications and data fused capabilities to the warfighter. C3D focuses on the ideation, development, implementation, testing, and analysis of various technical challenges ranging from Combined Joint All Domain C2 war fighting concepts to the challenges posed by the increasing lethality of modern contested, degraded environments of near-peer and peer adversaries.

Job

Purpose

The Data Scientist interprets and analyzes data to solve problems and sponsor needs, utilizing advanced algorithms in statistics, machine learning, and artificial intelligence for analyzing and classifying datasets. In addition, the Data Scientist extracts hidden information from large sources of raw data to deliver value to business stakeholders and applies state‑of‑art data mining techniques, conducts statistical analyses, builds high‑quality prediction models, and data visualizations.

The Data Scientist is also responsible for selecting features as well as building and optimizing classifiers using machine learning or statistical techniques. The Data Scientist creates a thorough plan for model validation and conducts A/B testing when required. This position requires a strong educational background in computer science and/or mathematics, particularly with an advanced degree. Additionally, the Data Scientist may perform physics‑based modeling, applied quantum algorithms, and artificial intelligence (AI).

Key Responsibilities
  • Extract and clean data
  • Create reports and visualizations
  • Proficient in R, Python, and/or Julia, also SAS, SPSS, and/or Tableau.
Additional Responsibilities
  • Apply mathematical and statistical techniques to analyze complex datasets and quantify uncertainty in model outputs.
  • Assist in designing experiments and studies, including sampling strategies and power analyses, under the guidance of senior faculty.
  • Implement statistical models (e.g., linear and generalized linear models, time‑series models, Bayesian methods) and evaluate their performance using appropriate diagnostics.
  • Develop and maintain reproducible analysis pipelines in Python or R, emphasizing transparent statistical assumptions and methods.
  • Create clear visualizations and quantitative summaries to communicate statistical findings to project teams and stakeholders.
Required

Minimum Qualifications
  • Successful completion of core coursework in probability, mathematical statistics, and at least one of: regression analysis, experimental design, time‑series analysis, or machine learning.
  • Demonstrated ability to implement statistical methods in Python or R, including data wrangling, model fitting, model evaluation, and visualization.
  • Solid understanding of statistical inference concepts such as confidence intervals, hypothesis testing, and p‑values, and when they are appropriate.
  • Strong quantitative reasoning, attention to detail, and commitment to data quality and reproducibility.
  • Effective written and verbal communication skills for explaining methods, assumptions, and results to technical team members.
Preferred Qualifications
  • Active Secret Clearance
  • Master’s degree in Statistics, Mathematics, Applied Mathematics, Biostatistics, or a…
Position Requirements
Less than 1 Year work experience
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