Data Scientist - TS/SCI required

Parsons Corporation•Aberdeen, MD

23h•$88,400 - $154,700•Onsite

About The Position

As a Data Scientist at Parsons, you will leverage advanced analytics and emerging technologies in support of mission-critical requirements for the Department of War and United States Army. Join a collaborative team of 500 professionals working across operations and technical disciplines, with a focus on Artificial Intelligence and Cloud Computing for advanced technology development, contributing to a diverse set of efforts over 5 years and a total value exceeding $600 million. The ideal candidate is innovative, highly skilled in data science methodologies, and adept at extracting actionable insights from complex datasets to support Army modernization and the warfighter.

Requirements

Bachelor’s to Master’s degree in a relevant field (e.g., Computer Science, Statistics, Mathematics, Engineering, or related discipline).
3–10+ years of professional experience in data science, analytics, or a related field.
TS/SCI is required
Experience with software integration or testing, including test plan and script development.
Proficiency in scripting languages such as Python or R, and familiarity with data science libraries and tools (e.g., Jupyter Notebook, Pandas, Numpy).
Experience with SQL, NoSQL, API development, ETL pipelines, and web application servers.
Demonstrated ability to apply complex mathematical and statistical concepts.
Experience with data mining, statistics, or graph algorithms to support analytics objectives.
Proficiency in using spreadsheets and visualization tools for data manipulation and presentation.

Nice To Haves

Relevant industry certifications (e.g., CompTIA Cloud Essentials, EMCDSA, Cloudera, CISSP, Microsoft certifications) are preferred.
Strong analytical, problem-solving, and communication skills.

Responsibilities

Design, develop, and implement data models, algorithms, and analytical solutions to address business and mission challenges.
Integrate, test, and validate data-driven applications and software tools.
Utilize scripting languages and statistical packages to analyze large structured and unstructured datasets.
Build and maintain ETL pipelines, APIs, and data interfaces to support analytics workflows.
Apply advanced mathematical, statistical, and operations research methods to solve complex problems.
Develop and present data visualizations, reports, and dashboards for technical and non-technical audiences.
Collaborate with stakeholders to identify data requirements and deliver actionable insights.
Stay current with emerging technologies and best practices in data science and analytics.