Poly

Peraton•Laurel, MD

2d•$176,000 - $282,000•Onsite

About The Position

Peraton is seeking a talented and skilled Data Scientist Engineers to join our team in Laurel, MD. A data scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.

Requirements

Bachelor's degree from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science) and five (5) years of experience analyzing datasets and developing analytics.
Five (5) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
An Active TS/SCI clearance with polygraph is required.

Nice To Haves

Familiarity with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) frameworks, agents, and agentic workflow.

Responsibilities

Develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets.
Prototype or consider several algorithms and decide upon final model based on suitable performance metrics.
Build models or develop experiments to generate data when training or example datasets are unavailable.
Generate reports and visualizations that summarize datasets and provide data-driven insights to customers.
Partner with subject matter experts to translate manual data analysis into automated analytics.
Implement prototype algorithms within production frameworks for integration into analyst workflows.
Produce data visualizations that provide insight into dataset structure and meaning.
Work 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.
Develop Al and machine learning models to address complex problems.
Develop and optimize Large Language Models (LLM) for various NLP tasks and information retrieval.
Utilize GPU-based computing resources to accelerate model training and deployment.
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.
Develop experiments to collect data or models to simulate data when required data are unavailable.
Develop feature vectors for input into machine learning algorithms.
Identify the most appropriate algorithm for a given dataset and tune input and model parameters.
Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices).
Oversee the development of individual analytic efforts and guide team in analytic development process.