Poly

Peraton•Laurel, MD

1d•Onsite

About The Position

Peraton is seeking a talented and skilled Data Scientist Engineer to join our team in Laurel, MD. This role involves developing machine learning, data mining, statistical, and graph-based algorithms to analyze datasets, prototyping and selecting optimal models, and creating visualizations to provide data-driven insights. The Data Scientist will partner with subject matter experts to automate manual data analysis and implement prototype algorithms into production frameworks for analyst workflows. This position requires an active TS/SCI clearance with polygraph.

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

An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Bachelor's degree.
A PhD from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience.
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.
Incorporate SME input into feature vectors suitable for analytic development and testing.
Develop AI 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 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.
Oversee the development of individual analytic efforts and guide team in analytic development process.