Data Scientist Level 4 Security Clearance

Position: Data Scientist Level 4 with Security Clearance
Weeghman & Briggs is seeking Data Scientists to join our growing team.

Location:

Annapolis Junction

Clearance Required:

TS/SCI w/ Polygraph Your effort and expertise are crucial to the success and execution of this impactful mission. This opportunity supports a team of Data Scientists, Cryptologic Computer Scientists, Cryptanalytic Computer Scientists, Cryptologic Cyber Planners, Intrusion Analysts, Protocol Analysts, Signals Analysts and Reverse Engineers, responsible for improving, protecting, and defending our Nation's Security.

Job Description:

* We are seeking a Data Scientist who is an established AI expert with demonstrable experience in designing and implementing sophisticated AI/ML and data science solutions across various domains within the customer environment. You will help to establish an authoritative role in a customer-prioritized and highly visible AI system that will be of critical use. You will need to to have experience designing and building customized capabilities to enable Retrieval Augmented Generation (RAG) for multiple enterprise data sets, agentic AI systems to automate and orchestrate decision-making actions across specialized AI resources, and Docker-based microservices, user-facing GUIs, and cloud-hosted services (Kubernetes architecture) hosted on AWS/Azure/Google service platforms.

attribution. The Level 4 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 feature 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 15 years of relevant experience.
* Associate's degree with 17 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).

College-level requirement, or upper-level math courses designated as elementary or basic do not count.
* 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.
* Experience with designing and building:
* Customized capabilities to enable Retrieval Augmented Generation (RAG) for multiple enterprise data sets.
* Agentic AI systems to automate and orchestrate decision-making actions across specialized AI resources.
* Docker-based microservices, user facing GUIs, and Cloud-hosted services (Kubernetes architecture) hosted on AWS/Azure/Google service platforms.
* Deep knowledge and experience in AI solutions and an ability to assess, evaluate, and implement the correct ML models for specific purposes and optimized performance.
* Experience generating, evaluating, training, and optimizing Machine Learning models (i.e. LLMs) for use in low-memory, low-resourced edge device environments.
* Proficient in the development and…