Data Scientist 1 - TS/SCI w/poly

Peraton; Maryland; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Heavily subsidized benefits coverage

25 days PTO annually

Bonus plan eligibility

Job summary

Peraton seeks a Data Scientist in Maryland to develop machine learning and analytical solutions for national security datasets. You will prototype algorithms, build scalable models, and generate data-driven insights for customers.

Collaboration with SMEs and deployment within analyst workflows are essential. The role requires implementing statistical and ML techniques, designing experiments, and producing meaningful visualizations while adhering to security protocols.

Qualifications

• Bachelor's degree in a quantitative discipline and five years of experience analyzing datasets using data analysis software such as R, Python, SAS, or MATLAB.
• An additional four years of experience in software development, cloud development, analyzing datasets, or developing analytics can substitute for a Bachelor's degree.
• Master's degree can substitute for two years of experience; PhD can substitute for four years.
• Experience with GPU-based computing resources to accelerate model training and deployment.
• Active TS/SCI security clearance with a current polygraph is required.

Responsibilities

• Develop machine learning, data mining, statistical and graph-based algorithms to analyze datasets and generate data-driven insights.
• Prototype or evaluate several algorithms and select final model based on performance metrics.
• Build models or experiments to generate data when training data is unavailable.
• Generate reports and visualizations that summarize datasets for customers.
• Collaborate with SMEs to translate manual data analysis into automated analytics.
• Implement prototype algorithms within production frameworks for integration into analyst workflows.
• Oversee one or more software development teams and ensure adherence to the development process.
• Produce data visualizations to reveal dataset structure and meaning.

Skills

Python

R

SAS

MATLAB

GPU computing

Education

Bachelor's degree in quantitative discipline

Master's degree substitutions for experience

Tools

None specified

Job description

Basic Qualifications:

• Bachelor's degree from an accredited college or university in quantitativediscipline (e.g., statistics, mathematics, operations research, engineering, or computer science) and 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 can be substituted for a Bachelor's degree.
  • A Master's degree in an accredited college or university can be substituted for two (2) years of experience. A PhD from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience.
• Experience with utilizing GPU-based computing resources to accelerate model training and deployment.
• Active TS/SCI security clearance with a current polygraph is required

Desired Qualifications:

• Expereince in one of the following:
  • 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.

Benefits:

• heavily subsidized employee benefits coverage for you and your dependents
• 25 days of PTO accrued annually up to a generous PTO cap
• eligibility to participate in an attractive bonus plan

Peraton offers enhanced benefits to employees supporting this critical National Security program, which include heavily subsidized employee benefits coverage for you and your dependents, 25 days of PTO accrued annually up to a generous PTO cap, and eligibility to participate in an attractive bonus plan.

The 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.

Other duties may include:

• Oversee one or more software development teams and ensure the work is completedin accordance withthe constraints of the software development process being used on anyproject.
• Produce data visualizations that provide insight into dataset structure and meaning.
• Work with subject matters experts (SMEs) toidentifyimportant informationin 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 andoptimizeLarge Language Models (LLM) for various NLP tasks and information retrieval.
• Develop and implement statistical, machine learning, and heuristic techniques to createdescriptive, predictive, and prescriptive analytics.
• Develop statistical tests to make data-driven recommendations and decisions.
• Develop experiments to collect data or models to simulate data whenrequireddata areunavailable.
• Develop feature vectors for input into machine learning algorithms.
• Identify the mostappropriate algorithmfor a given dataset and tune input and model parameters.
• Evaluate andvalidatethe performance of analytics using standard techniques and metrics (e.g.cross validation, ROC curves, confusion matrices).
• Oversee the development of individual analytic efforts and guideteamin analyticdevelopment process.