Are you VIGILANT about 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 to design and deploy machine‑learning models, build advanced statistical and predictive analytics, and leverage large‑scale data processing tools such as Spark and cloud‑based platforms.  The role emphasizes applying AI/ML techniques to assess and derive insights from large datasets, requiring strong competencies in data modeling, computational mathematics, and both qualitative and quantitative analytic methods.  Responsibilities also include providing advanced discovery support through analytical prototyping, scripting, workflow automation, data visualization, statistical analysis, and use of TechSIGINT technologies. Success in this position requires an adaptable mindset and the ability to quickly incorporate new tools, technologies, and methods as mission needs evolve.  A successful candidate will ideally bring prior experience as a DNEA, TDNA, targeteer, or with broader discovery skillsets, particularly within telecom, mobile, and access‑discovery environments. 

The Level 2 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 Customer 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 3 years of relevant experience, associate’s degree with 5 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