Data Scientist - Python, Jupyter, Spark (2026-0177) with Security Clearance
Why This Role Stands Out
This hybrid Data Scientist role offers a highly competitive salary and the opportunity to leverage your Python, Jupyter, and Spark expertise to drive impactful cybersecurity policy decisions for federal agencies. You'll thrive here if you possess strong analytical foundations and a passion for uncovering insights within large datasets, contributing to a reputable and employee-owned company. Don't miss the chance to advance your career in this dynamic and rewarding position.
Quick Overview
Job Description
Acclaim Technical Services, founded in 2000, is a leading language, operations, and technology services company supporting a wide range of U.S. Federal agencies. We are an Employee Stock Ownership Plan (ESOP) company, which is uncommon within our business sector. We see this as a significant strength, and it shows: ATS is consistently ranked as a top workplace among DC area firms and continues to grow.
We are actively recruiting for a Data Scientist with TS/SCI w/ Poly tosupport our Defense and Homeland Security Division in Annapolis Junction, MD In this role, you will support the understanding, identification, and mapping of large-scale datasets. You will integrate AI techniques to help develop and deliver cybersecurity policy to mission partners and document and assess metrics to help leadership make informed decisions. Experience with Python, Jupyter, Spark, data curation and visualizations/dashboards, and understanding of generative AI techniques strongly preferred.
The Data Scientist shall possess the following capabilities
- Foundations: (Mathematical, Computational, Statistical).
- Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility).
- Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations).
- Ability to make and communicate principal conclusions from data using elements of mathematics, statistics, computer science, and applications-specific knowledge.
- Ability to use analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in Government data holdings.
- Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.
- Effectively communicate complex technical information to non-technical audiences.
Qualifications
- Bachelor's Degree with 10 years of relevant experience, associate's degree with 12 years of experience may be considered for individuals with in-depth experience that is clearly related to the position.
- Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming, data structures, data mining, artificial intelligence).
- Broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university.
- Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least on high level language (e.g.
Python), statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. The salary range for this position is between $180,000 - $200,000
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