Category: Development and implementation

Subcategory: Data and analytics

Data science - DATS

Applying mathematics, statistics, data mining and predictive modelling techniques to gain insights, predict behaviours and generate value from data.

Levels:

Level 2:
Description: Under routine supervision, applies specified data science techniques to data. Analyses and reports findings and addresses simple issues, using algorithms included within standard software frameworks and tools.

Level 3:
Description: Applies standard data science techniques to new problems and datasets using specialised programming techniques. Identifies and selects appropriate data sources and prepares data to be used by data science models. Evaluates the outcomes and performance of data science models. Identifies and implements opportunities to train and improve models and the data they use. Publishes and reports on model outputs to meet customer needs and conform to agreed standards.

Level 4:
Description: Investigates problems and datasets to assess the usefulness of data science solutions. Applies diverse data science techniques and specialised programming languages. Understands and applies rules and guidelines specific to the industry and business, and anticipates risks and other implications of modelling. Selects, acquires and integrates data for analysis. Formulates hypotheses and evaluates data science models. Advises on the effectiveness of specific techniques based on analysis findings and research. Contributes to the development, evaluation, monitoring and deployment of data science solutions.

Level 5:
Description: Plans, coordinates and drives all stages of the development of data science solutions. Provides expert advice to evaluate the problems to be solved and the need for data science solutions. Identifies and justifies what data sources to use or acquire. Specifies and applies appropriate data science techniques and specialised programming languages. Critically reviews the benefits and value of data science techniques and tools and recommends improvements. Contributes to developing policy, standards and guidelines for developing, evaluating, monitoring and deploying data science solutions.

Level 6:
Description: Champions and leads the introduction and use of data science to drive innovation and business value. Develops and drives adoption of and adherence to organisational policies, standards, guidelines and methods for data science. Sets direction and leads in the introduction and use of data science techniques, methodologies and tools. Leads the development of organisational capabilities for data science. Plans and leads strategic, large and complex data science initiatives to generate insights, create value and drive decision-making.