Data Scientist 4

Are youVIGILANTabout your career? RealmOne definitely is!

RealmOne was built on the principle that people matter first and foremost. We believe in providing a strong work/life balance by investing in our employees and encouraging professional and personal growth. We do this by offering exceptional benefits, flexible schedules, and the tools necessary to achieve success through paid training, mentoring, and the opportunity to work alongside top-notch industry professionals.

Join us on this journey as we execute this mission-critical contract providing high-end analytics and data science services within the REALM of cybersecurity.

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 will be performing exploratory data analysis (EDA) on large, complex datasets to derive critical insights and respond to requests for information (RFIs). This position requires strong foundations in mathematical modeling and statistical analysis to support intelligence-driven objectives. The analyst will play a key role in modernizing the analytic lifecycle by integrating AI‑enabled workflows and automated data‑processing solutions, effectively replacing legacy processes with AI‑powered tradecraft. The position also serves as a vital bridge between complex technical data and decision‑makers, translating findings clearly across technical documentation and collaborative forums. Candidates should demonstrate proficiency in Python and PySpark (with R, SQL, and Scala as advantageous additions), AI/ML experience with frameworks such as PyTorch, TensorFlow, and Scikit‑Learn, and architectural familiarity with RAG, prompt engineering, or LoRa workflows. Experience with LangChain, LlamaIndex, and Hugging Face Transformers is beneficial, as is knowledge of vector databases and data‑visualization platforms such as Tableau, Seaborn, Matplotlib, and Plotly. Any DevOps experience—including Git, Docker, Kubernetes, or Jupyter Notebooks—will be considered a plus.

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.   

Position requires active Security Clearance with appropriate Polygraph