Data Scientist 3

Gormat

$100K — $130K *
Aerospace & Defense
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree with 10 years of relevant experience or an Associate's degree with 12 years of experience.
  • Degree in Mathematics, Applied Statistics, Data Science, Computer Science, or a related field with advanced coursework.
  • Proven experience in designing and implementing machine learning models, advanced analytics, and statistical analysis.
  • Skilled in data management, curation, visualization, and workflow automation with proficiency in at least one high-level programming language (e.g., Python).
  • Demonstrated ability to extract insights from large, complex datasets using quantitative and qualitative methods.
  • Must possess an active TS/SCI with Full Scope Poly clearance.

Responsibilities

  • Perform technical analysis on malware to determine functionality, capability, and indicators of compromise.
  • Document findings to support malware detection, signature creation, and mitigation efforts.
  • Improve workflows through automation, data aggregation, and custom analytics in support of East Asia Cyber initiatives.
  • Develop and apply statistical models and data-driven methods to assess and interpret large datasets.
  • Communicate complex technical insights clearly to non-technical audiences and inform decision-making.

Benefits

  • RCES funded project supporting East Asia Cyber operations.
Full Job Description
Job Description:

Performs technical analysis for malicious, in order to ascertain functionality and capability, assist with attribution and identification of indicators of compromise. Provide information and documentation that enables malware detection, signature creation, and mitigation.

  • RCES funded requiement supporting East Asia Cyber. Focused on workflow improvement and automation, data aggregation, and custom data analytics.

The Level 3 Data Scientist shall possess the following capabilities:

Employ some combination (2 or more) of the following skill areas:
  • 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 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. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting Government 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.


Must Have an ACTIVE TS/SCI With Full Scope Poly.

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