Data Scientist Security Clearance

Gormat is seeking a Data Scientist with experience leveraging AI/ML techniques for optimization, automation, and collection processing, and a willingness to teach AI/ML skills to more junior Data Scientists. You will need to be proficient with API interaction including reading/using/building tools to retrieve data. Experience with Pandas data frames and aggregation using Python is required. Data visualization capabilities with Plotly, Shapely, or Geo Pandas, AMOD tool proficiency and an understanding of dataflow, and Splunk, Kibana, SQL, ELK stack, or Networking experience is a plus.

Front end web development using Boot Strap (HTML) or Pyodide is a plus.

• 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 application‑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.
• Experience leveraging AI/ML techniques for optimization, automation and collection processing (Willing to send to courses to teach as a tradeoff for a strong DS without it).
• Requires proficiency with API interaction; reading/using/building tools to retrieve data.
• Data frame and aggregation experience using Python is required.
• Data Visualization capabilities with Plotly, Shapely, Geo Pandas is a plus.
• XKS/DX proficiency and an understanding of dataflow is a plus.
• Splunk, SQL, Elastic, Kibana or Networking experience is a plus.
• Front end web development using bootstrap (HTML) or Pyodide are also a plus.
• Having experience or background with SIGINT data collection is a plus.
• TS/SCI with polygraph is required.

• Bachelor's Degree with 10 years of relevant experience, associate's degree with 12 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).
• 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.
• Capable of applying and developing best tradecraft practices for deep analysis of network‑centric data from a variety of sources and extracting actionable intelligence, including pattern recognition and attribution.