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# Data Scientist, Level 1

- **Company:** WOOD Consulting Services, Inc.
- **Location:** Fort Meade, MD, United States (Remote available)
- **Salary:** $138,200.0 - $152,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Computer Programming, Data Visualization, R (Programming Language), Statistical Hypothesis Testing, Python (Programming Language), MATLAB, Machine Learning, Raw Data, SAS (Software), SQL Databases, Information Technology, Data Analytics
- **Published:** August 20, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18010184?backUrl=%2Fcareer%2F18010184%2FData-Scientist-Level-1-Maryland-Fort-Meade

## About the Role

This position requires all candidates to be U.S. Citizens and possess an active TS/SCI Security Clearance with a Polygraph., Required Education & Years of Experience:

 * Requires a Bachelor's degree in a relevant discipline (e.g., statistics, mathematics, operations research, and engineering or computer science) from an accredited college or university, and four (4) years of experience analyzing datasets and developing analytics and two (2) year of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
 + A Master's degree in relevant discipline may be substituted for two (2) years of relevant experience analyzing datasets anddeveloping analytics, and one (1) year of relevant experience programming with data analysis software such as R, Python, SAS, or MATLAB.
 + In lieu of a Bachelor's Degree, an additional four (4) years of relevant experience may be substituted for a total of eight (8) years of relevant experience analyzing datasets and developing analytics, and two (2) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.

## Description

Produce data visualizations that provide insight into dataset structure and meaning.

 * Collaborate with subject matters experts (SMEs) to identify important information in raw data
and develop scripts that extract this information from a variety of data formats (e.g., SQL tables,
structured metadata, network logs).

 * Incorporate SME input into feature vectors suitable for analytic development and testing.
 * Translate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes.
 * Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics.
 * Develop statistical tests to make data-driven recommendations and decisions.


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