Nyla Technology Solutions
Data Scientist Level 2
Nyla Technology Solutions, Annapolis, Maryland, United States, 21403
We are pursuing individual(s) for the position of
Data Scientist Level 2 . If this position sounds like a good fit and you have a track record of delivering solid results, please apply.The Data Scientist will employ some combination skill areas including Foundations (Mathematical, Computational, Statistical), Data Processing (Data management and curation, data description and visualization, workflow and reproducibility), and/or Modeling, Inference, and Prediction (Data modeling and assessment, domain-specific considerations).The ideal candidate for this job is a self-starter. The Data Scientist 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. 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 collection, processing, storage, and analytic capabilities and limitations.Required Skills
Strong background in scripting and developmentPython, Abascus/ KibinaQualifications:
A Bachelor's degree and 3 years of relevant experience. An Associate's degree plus 5 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., algorithms, 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.Note: 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 one area is strongly preferred.
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Data Scientist Level 2 . If this position sounds like a good fit and you have a track record of delivering solid results, please apply.The Data Scientist will employ some combination skill areas including Foundations (Mathematical, Computational, Statistical), Data Processing (Data management and curation, data description and visualization, workflow and reproducibility), and/or Modeling, Inference, and Prediction (Data modeling and assessment, domain-specific considerations).The ideal candidate for this job is a self-starter. The Data Scientist 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. 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 collection, processing, storage, and analytic capabilities and limitations.Required Skills
Strong background in scripting and developmentPython, Abascus/ KibinaQualifications:
A Bachelor's degree and 3 years of relevant experience. An Associate's degree plus 5 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., algorithms, 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.Note: 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 one area is strongly preferred.
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