Data Science Associate Jobs in Catonsville, MD (NOW HIRING)

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 who is familiar with the customer's enterprise data processing pipeline. You will be working to integrate AI into malware detection and malware analysis capabilities. The Level 3 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).
* Devise strategies for extracting meaning and value from large datasets. Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge. Through 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 features and limitations inherent in DOD 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. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting DOD collection, processing, storage and analytic capabilities and limitations.Qualifications: * Bachelor's Degree with 10 years of relevant experience.
* Associates degree with 12 years of relevant experience.
* 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. Note: A 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 one 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 in more than one area is strongly preferred. Position requires active Security Clearance with appropriate Polygraph