Data Scientist (2,3,4)

Develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets. Prototype or consider several algorithms and decide upon final model based on suitable performance metrics. Build models or develop experiments to generate data when training or example datasets are unavailable. Generate reports and visualizations that summarize datasets and provide data-driven insights to customers. Partner with subject matter experts to translate manual data analysis into automated analytics. Implement prototype algorithms within production frameworks for integration into analyst workflows.

Experience with software development, either an open-source enterprise software development stack (Java/Linux/Ruby/Python) or a Windows development stack (.NET, C#, C++). Experience with data transport and transformation APIs and technologies such as JSON, XML, XSLT, JDBC, SOAP and REST. Experience with Cloud-based data analysis. Experience with visual analytic tools and experience with entity extraction and machine learning, algorithm analysis, and data clustering.

Basic Qualifications: 

• 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
• 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 oflinear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. 
• Active TS SCI security clearance with a current polygraph is required 

Note: A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university. 

Level 2:

Bachelor’s Degree with 3 years of relevant experience
Associates degree with 5 years of relevant experience

Level 3:

Bachelor’s Degree with 10 years of relevant experience
Associates degree with 12 years of relevant experience

Level 4:

Bachelor’s Degree with 15 years of relevant experience
Associates degree with 17 years of relevant experience

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