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Data Scientist Level 3

Aurora, CO, United States

Base-2 Solutions is looking for a Data Scientist Level 3.

Education Required

Bachelor's degree plus 10 years of relevant experience.

Associate's degree plus 12 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position.

Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science.

A degree in a related field (e.g., 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, and life) may be considered if it includes a concentration of coursework (typically 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., algorthms, programming, data structures, data mining, artificial intelligence). College-level Algebra or other math courses intended to meet a basic college level requirement, or upper level math courses designated as elementary or basic do not count.

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

Description of Relevant Experience Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorthms, 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 reproductibility, data management and curation, data modeling and assessment (e.g. model selection, evaluation, and sensitivity analysis), experience as a data scientist working to support a single or multiple domain areas, and/or software engineering.

Experience in more than three areas is strongly preferred.

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