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Date Science and Analytics Category National Occupational Standard Framework for Data & Artificial Intelligence SKILLS Skill in conducting queries and developing algorithms to analyze data structures. Skill in creating and utilizing mathematical or statistical models. Skill in generating queries and reports. Skill in using programming and data tools to collect, preprocess, and analyze data from various sources. Skill in identifying hidden patterns or relationships. Skill in performing analytical methods including exploratory data analysis, statistical testing, sensitivity analysis, outlier identification and removal techniques. Skill in developing machine understandable semantic ontologies. Skill in Regression Analysis (e.g., Hierarchical Stepwise, Generalized Linear Model, Ordinary Least Squares, Tree-Based Methods, Logistic). Skill in using basic descriptive statistics and techniques (e.g., normality, model distribution, scatter plots). Skill in the use of design modeling (e.g., unified modeling language). Skill in data mining techniques (e.g., searching file systems) and analysis. Skill to identify sources, characteristics, and uses of the organization’s data assets. D-An-S01 D-An-S02 D-An-S03 D-An-S04 D-An-S05 D-An-S06 D-An-S07 D-An-S08 D-An-S09 D-An-S10 D-An-S11 D-An-S12 KNOWLEDGE Knowledge of computer networking concepts & protocols, and network security methodologies. Knowledge of computer programming principles. Knowledge of data administration and data standardization policies. Knowledge of data mining and data warehousing principles. Knowledge of database management systems, query languages, table relationships, and views. Knowledge of sources, characteristics, and uses of the organization’s data assets. Knowledge of the capabilities & functionality associated with various technologies for organizing and managing information (e.g., databases, bookmarking engines). Knowledge of advanced data remediation security features in databases. Knowledge of database access application programming interfaces. Knowledge of applications that can log errors, exceptions, and application faults & logging. D-An-K01 D-An-K02 D-An-K03 D-An-K04 D-An-K05 D-An-K06 D-An-K07 D-An-K08 D-An-K09 D-An-K10 National Occupational Standard Framework for Data & Artificial Intelligence - A bachelor's degree in computer science, statistics, business information systems, information managment or a related discipline is usually required. - A master's or doctoral degree in data science, economics, science (if curricula contain data analysis) or a related quantitative field is usually preferred. EDUCATION EDUCATION - Experience in data analysis techniques and statistical methodologie is usually required. EXPERIENCE EXPERIENCE ABILITIES ABILITIES Ability to carry out data quality control, validation and linkage. Ability to produce clear graphical representations and data visualisations. Ability to work with complex data structures using high-level programming languages. Ability to dissect a problem and examine the interrelationships between data that may appear unrelated. Ability to identify basic common coding flaws at a high level. Ability to use data visualization tools (e.g., Flare, HighCharts, AmCharts, D3.js, Processing, Google Visualization API, Tableau, Raphael.js). Ability to accurately and completely source all data used in intelligence, assessment and/or planning products. Ability to multi-task, collaborate with peers, customers, and management to accomplish a variety of different tasks in a constantly changing environment. D-An-A01 D-An-A02 D-An-A03 D-An-A04 D-An-A05 D-An-A06 D-An-A07 D-An-A08 National Occupational Standard Framework for Data & Artificial Intelligence