Data Scientist 1 - TS/SCI w/poly
$146,000–$234,000 year
On-siteLaurel, Maryland, United States
Job Summary
Develop machine learning, data mining, and statistical algorithms to analyze datasets and generate data-driven insights for customers. Build models to simulate data when training sets are unavailable and produce visualizations summarizing dataset structure. Partner with subject matter experts to extract information from raw data formats and translate manual analysis into automated workflows. Evaluate analytics performance using standard metrics and guide teams in analytic development processes. Design and optimize Large Language Models for NLP tasks and implement statistical techniques for descriptive, predictive, and prescriptive recommendations. This role requires a Bachelor's degree in a quantitative discipline and five years of experience in data analysis, with an additional four years in software development substitutable. Active TS/SCI clearance with a polygraph is mandatory. Salary ranges from $146,000 to $234,000. Peraton supports critical national security missions across land, sea, space, air, and cyberspace domains.
Required Qualifications
- Bachelor's degree from an accredited college or university in quantitative discipline (e.g., statistics, mathematics, operations research, engineering, or computer science)
- five (5) years of experience analyzing datasets and developing analytics using 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
- A Master's degree in an accredited college or university
- A PhD from an accredited college or university in a quantitative discipline
- Experience with utilizing GPU-based computing resources to accelerate model training and deployment
- Active TS/SCI security clearance with a current polygraph
Desired Qualifications
- Designing/implementing machine learning, data science, and advanced analytical algorithms capabilities developed in at least one high-level programming 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
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