Data Scientist 4

Gormat • Annapolis Junction, MD

8d

About The Position

We are seeking a Data Scientist proficient in Python and experienced in automating workflows, data manipulation, and visualization using Jupyter Notebooks. This role involves leveraging Python expertise to streamline processes and create insightful visualizations for data-driven decision-making. 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). 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. Primary success marker is extensive experience with Metrics. Requires Python proficiency with Jupyter notebooks and demonstrated performance using Pandas for Data Frames. Candidate will identify access technical, technical gaps, and data driven opportunities for optimization across existing organizational tradecraft. Requires developing and maintaining data ontology dictionaries, systematic interdivisional metrics capture, data analysis, data visualization, workflow automation solutions and great communication skills to interface with teams and present results. Requires proficiency with API interaction; reading/using/building tools to retrieve data. Data Visualization with Shapely, Plotly, Tableau, Power BI, or Matplotlib/Seaborn is a plus. Any exp with Splunk, Kibana, SQL, JAVA, C++, HTML w bootstrap exp or Pyodide are also a plus. Having broad experience with SIGINT data collection or completing 450/451 is a plus.

Requirements

• Python proficiency with Jupyter notebooks
• Demonstrated performance using Pandas for Data Frames
• Proficiency with API interaction; reading/using/building tools to retrieve data.
• Great communication skills
• Bachelor's Degree with 15 years of relevant experience. Associates degree with 17 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.
• TS/SCI with polygraph is required.

Nice To Haves

• Data Visualization with Shapely, Plotly, Tableau, Power BI, or Matplotlib/Seaborn is a plus.
• Any exp with Splunk, Kibana, SQL, JAVA, C++, HTML w bootstrap exp or Pyodide are also a plus.
• Having broad experience with SIGINT data collection or completing 450/451 is a plus.

Responsibilities

• 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.
• Identify access technical, technical gaps, and data driven opportunities for optimization across existing organizational tradecraft.
• Developing and maintaining data ontology dictionaries, systematic interdivisional metrics capture, data analysis, data visualization, workflow automation solutions
• Interface with teams and present results.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1-10 employees