Data Scientist III with Security Clearance

Black Eagle Defense; Fort Meade (MD); On-site; USD 128,000 - 185,000; Full time

Job summary

Black Eagle Defense seeks a Data Scientist III to devise strategies for extracting meaning from large datasets and to communicate principled conclusions using mathematics, statistics, CS, and domain knowledge.

The role includes developing and implementing qualitative and quantitative methods to characterize and assess diverse data holdings, translating mission questions into technical requirements, and guiding others in deriving actionable insights from analysis.

Qualifications

• Bachelor's degree with extensive related experience, or Associate degree with deep relevant work.
• Experience in ML, data science, statistics, data management, and software engineering.
• Proficiency in Python and strong mathematical background required.

Responsibilities

• Devise strategies to extract meaning from large datasets and communicate results.
• Translate mission needs into technical requirements and advise on analysis approaches.

Skills

Foundations

Data Processing

Modeling/Inference/Prediction

Education

Bachelor's degree

Associate's degree

Tools

Python

Job description

Job Description

SALARY RANGE $128,000 - $185,000/year DUTIES As a successful candidate for the Data Scientist III role, you will 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 NSA/CSS data holdings. Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others in withdrawing 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 NSA/CSS collection, processing, storage, and analytic capabilities and limitations.

Required Skills

SKILLS Employ some combination (2 or more) of the following skill areas: I. Foundations: (Mathematical, Computational, Statistical) II. Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility) III. Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)

Qualifications

A Bachelor's Degree with 10 years of relevant experience or an 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). College-level requirements, 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. 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 three areas is strongly preferred.

Additional Requirements

• Accurately and automatically tokenize language data with spoken or written origins
• Develop automated solutions for the annotation of language data with parts of speech information, and improved existing models by scoring performance against human-generated annotations for speech and text
• Demonstrated NLP experience