Data Scientist 3

Gormat

158d

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 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. Requires compiling various data sources via computer scripting, statistical analysis, data modeling, etc. This position requires being able to develop rapid prototypes and analytics to show metrics on sensor performance. A SIGINT background is a strong foundation for this team. PROFORMA or other RF experience and/or 451/452 is a nice to have.

Requirements

Proficient in Python
Experience in automating workflows
Experience in data manipulation
Experience in visualization using Jupyter Notebooks
Foundations in Mathematical, Computational, and Statistical concepts
Data management and curation skills
Data description and visualization skills
Workflow and reproducibility skills
Data modeling and assessment skills
Domain-specific considerations
Experience in designing/implementing machine learning
Experience in data science
Experience in advanced analytical algorithms
Programming skills (skill in at least one high-level language, e.g. Python)
Statistical analysis experience (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models)
Data management experience (e.g. data cleaning and transformation)
Data mining experience
Data modeling and assessment experience
Artificial intelligence experience
Software engineering experience
TS/SCI with polygraph clearance

Nice To Haves

SIGINT background
PROFORMA or other RF experience
451/452 experience

Responsibilities

Automating workflows
Data manipulation
Visualization using Jupyter Notebooks
Streamlining processes
Creating insightful visualizations for data-driven decision-making
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
Develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets
Translate practical mission needs and analytic questions related to large datasets into technical requirements
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
Compiling various data sources via computer scripting, statistical analysis, data modeling, etc.
Develop rapid prototypes and analytics to show metrics on sensor performance