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# Data Scientist Stf - E4

- **Company:** Lockheed Martin
- **Location:** Annapolis Junction, MD, United States
- **Experience:** Experienced
- **Salary:** $135,700.0 - $251,900.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Cloud Computing, Cloud Engineering, Data Mining, Distributed Systems, R (Programming Language), Python (Programming Language), MATLAB, Machine Learning, Natural Language Processing, SAS (Software), Software Engineering, Text Mining, Deep Learning, Numerical Computing, Information Technology, Machine Learning Operations
- **Published:** November 1, 2026
- **Apply:** https://www.nexxt.com/job.asp?id=3485666123&tx=JL1913FFK&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

Desired Skills

Experience with MLOPS and Data Scientist

Bachelor's degree or higher from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science). A minimum of ten (10) years of experience in two (2) or more of the following: designing/implementing machine learning, data mining, advanced analytical algorithms, advanced statistical analysis, artificial intelligence, or software engineering with data analysis software such as R, Python, SAS, or MATLAB. An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Bachelor's degree.

A Master's Degree from an accredited college or university in a quantitative discipline can be substituted for two (2) years of experience for a total of eight (8) years of experience required. A Doctoral Degree from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience for a total of six (6) years of experience required.

## Description

Perform exploratory research and analysis to identify novel and meaningful patterns in data and uses statistical methods to reject or accept proposed hypotheses about relationships or latent predictive factors discovered through their work to provide business value. Uses a combination of tools, technologies, and numerical computing systems (i.e.: GPU processing, distributed computing, highly parallel coding, cloud computing, machine learning, visualization, system modelling and simulation) to achieve results. Areas of expertise should include several of the following: applied statistics, text mining, natural language processing, deep learning, optimization, and other similar fields. Work on datasets with applied statistics and machine learning algorithms; Use exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data sets and discover opportunities in datasets to support decision-making; Develop predictive models and new algorithms to
solve data / business problems; Understand the math and statistics behind the models and interpret, extrapolate, and prescribe from data to deliver actionable recommendations using effective visualizations