Data Scientist (All Levels)
Annapolis Junction, MDSecurity Clearance:
- A current government clearance, background investigation, and polygraph are required.
OPS Consulting is seeking qualified candidates to 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. 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 NSA/CSS collection, processing, storage and analytic capabilities and limitations.Requirements:
- A Bachelors Degree inMathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science
- 3, 10 or 15 years of relevant experience
- 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) and skill in at least one mid-level language (e.g. C)), data mining, advanced statistical analysis (e.g. statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations (e.g. numerical methods, graph theory), artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g. model selection, evaluation, and sensitivity analysis), experience as a data scientist working to support single or multiple domain areas, ability to quickly acquire needed expertise on a new application in a new domain area, and/or software engineering. Experience in severalareas is strongly preferred.