Job DutiesEmploy some combination (2 or more) of the following skill areas:Foundations: (Mathematical, Computational, Statistical)Data Processing: (Data management and curation, data description and visualization, workflow, and reproducibility)Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)Devise strategies for extracting meaning and value from large datasetsMake and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application-specific knowledgeThrough analytic modeling, statistical analysis, programming, and/or other 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 customer data holdingsTranslate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist other with drawing appropriate conclusions from the analysis of such dataEffectively communicate complex technical information to non-technical audiencesMake informed recommendations regarding competing technical solutions by maintaining awareness of constantly shifting collection, processing, storage and analytic capabilities and limitationsRequired Skills:US Citizens OnlyActive TS/SCI Clearance and Polygraph requiredInformation Assurance Certification may be required Minimum of three (3) years of relevant experience and a Bachelor’s degree or five (5) years of relevant experience and an Associate’s degree required.  Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer ScienceA broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/universityRelevant experience must be two of more of the following:Designing/implementing machine learningData scienceAdvanced analytical algorithmsProgramming (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 miningData modeling and assessmentArtificial intelligenceSoftware engineering___________________________________________________________________________________________________
IntelliGenesis is committed to the fair and equal employment of individuals with disabilities. It is the Company’s policy to reasonably accommodate qualified individuals with disabilities unless the accommodation would impose an undue hardship on the organization. In accordance with the Americans with Disabilities Act (ADA) as amended, reasonable accommodations will be provided to qualified individuals with disabilities, when such accommodations are necessary, to enable them to perform the essential functions of their jobs or to enjoy the equal benefits and privileges of employment. This policy applies to all applicants for employment and all employees.