Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility)
Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)
AI/ML experience combined with CNE familiarity
Python required
Data normalization and visualization
Math and statistics background
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
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
Other
Bachelor's Degree with 10 years of relevant experience
Associates degree with 12 years of relevant experience
Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming, statistical analysis, data management, data mining, data modeling and assessment, artificial intelligence, and/or software engineering
College-level requirement, or upper-level math courses designated as elementary or basic do not count
A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university
