JOB TITLE: DATA ANALYTICS TRAINEE

JOB CODE: 10600

SERIES NATURE OF WORK: The Data Analytics Specialist job series describes professional work that combines the disciplines of statistics, business analysis, and computer programming to design, develop, deliver, and maintain analytic applications and solutions.

DEFINITION: This is entry level training work researching, learning, and applying varied quantitative analysis and computer programming methods to manage, prepare, analyze, and visualize data.

An employee in this job receives structured and on-the-job training designed to develop an understanding and competence in quantitative frameworks, software tools, and domain knowledge to support the maintenance and development of analytic applications and solutions for an agency. An employee may initially perform a limited range of duties, such as assisting in collecting and preparing data, translating business requirements, researching quantitative analysis or coding alternatives, or maintaining data analytics solutions. Work will become increasingly more complex as learning progresses and technical proficiency is acquired. Work is performed under direct supervision. A supervisor assigns work and reviews assignments, in progress and upon completion, for development of competence in current quantitative frameworks, software tools, and analytic applications.

EXAMPLES OF WORK: (NOTE: The examples of work are representative of the work, but every position classified to this job may not perform all examples of work listed. Conversely, this is not an all-inclusive list of work examples.)

• Participates in a structured, on-the-job training program to develop proficiency in preparing, analyzing, and presenting data to meet the business needs.

• Assists in translating business requirements into analytic project specifications to include data set acquisition, data preparation, quantitative methodology, computer programming, or technology requirements.

• Assists in developing logic and coding to clean, merge, and prepare structured and unstructured data from disparate sources to ensure data consistency and integrity.

• Assists in the research of data management, quantitative analysis frameworks, and programming and visualization tools to address specific data problems or build application functionality.

• Assists in monitoring algorithms and models for reliability, investigates issues, and reviews findings with higher level analyst or supervisor.

• Assists in the development of data visualizations that illustrate insights and findings from data analysis.

• Assists in evaluating and assessing data collection methodologies, survey designs, and collection tools necessary to develop analytic solutions.

• Prepares documentation for completed assignments including computational logic, data formats, metadata, and methodologies used for creation, validation, analysis, or visualization of data.

• Participates in the development and implementation of training plans for users of analytical applications.

• Assists in providing technical and analytic support to end users of analytic applications and solutions.

• Performs related work as required.

ENTRY LEVEL KNOWLEDGES, SKILLS, AND ABILITIES:

• Knowledge of statistical, mathematical, and quantitative analysis concepts.

• Knowledge of data management fourth generation languages (4GL) as they apply to the preparation, analysis, or visualization of data.

• Knowledge of the use and functionality of Microsoft Office Suite software.

• Ability to think critically and solve business problems.

• Ability to communicate effectively orally.

• Ability to communicate effectively in writing.

• Ability to establish and maintain effective working relationships.

MINIMUM EXPERIENCE AND TRAINING: (NOTE: Based on the Entry Level Knowledges, Skills, and Abilities):

• One year of professional quantitative analytical experience utilizing data preparation, statistical analysis, or data visualization software programs and a bachelor’s degree in statistics, applied mathematics, computer science, data science, economics, actuarial science, geographic information systems (GIS), biostatistics, or a related STEM field (science, technology, engineering, and mathematics);

Thirty (30) graduate credits in data analytics or a closely related field may be substituted for the required experience;

or

• An equivalent combination of experience and training.