iNovex
Data Scientist 3 (Baltimore, MD)
iNovex, Columbia, Maryland, United States, 21046
Qualifications
Foundations: (Mathematical, Computational, Statistical)Bachelor's Degree with 10 years of relevant experienceAssociates degree with 12 years of relevant experienceBachelor's Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. Degrees in related fields (Computer Information Systems, Engineering), or physical/hard sciences (e.g. physics, chemistry, biology, astronomy) may be considered if they include at least 5 advanced Mathematics courses (typically 300 level or higher) and/or computer science courses (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.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.Position requires a security clearance with successful Polygraph.Responsibilities
Data extract, transform, load.Utilize various databases and scripting languages to load, extract, and parse large amounts of data.Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility).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 data holdings.Translate practical mission needs and analytic questions related to large datasets into technical requirements and 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 data collection, processing, storage, and analytic capabilities and limitations.
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Foundations: (Mathematical, Computational, Statistical)Bachelor's Degree with 10 years of relevant experienceAssociates degree with 12 years of relevant experienceBachelor's Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. Degrees in related fields (Computer Information Systems, Engineering), or physical/hard sciences (e.g. physics, chemistry, biology, astronomy) may be considered if they include at least 5 advanced Mathematics courses (typically 300 level or higher) and/or computer science courses (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.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.Position requires a security clearance with successful Polygraph.Responsibilities
Data extract, transform, load.Utilize various databases and scripting languages to load, extract, and parse large amounts of data.Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility).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 data holdings.Translate practical mission needs and analytic questions related to large datasets into technical requirements and 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 data collection, processing, storage, and analytic capabilities and limitations.
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