Leads the introduction and use of data science and analytics to drive innovation and business value.
SFIA Skills: Data and analytics
Capability development (Level 6)
Leads the development of organisational capabilities for data science and analytics.
Model evaluation and advice (Level Four)
Develops data hypotheses and methods and evaluates analytics models. Advises on the effectiveness of specific techniques based on project findings and comprehensive research.
Model evaluation and advice (Level Five)(DATS)
Provides expert advice to evaluate the problems to be solved and the need for data science solutions.
Model evaluation and advice (Level Three)(DATS)
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 conforming to agreed standards.
Data pipelines and stores (Level 6)(DENG)
Plans and leads data engineering activities for strategic, large and complex programmes.
Data pipelines and stores (Level 5)(DENG)
Plans and drives data engineering solution development ensuring that solutions balance functional and non-functional requirements.
Data pipelines and stores (Level 4)(DENG)
Creates and maintains data pipelines to connect data within and between data stores, applications and organisations — engineering solutions may be on-premise, cloud-based or hybrid.
Data pipelines and stores (Level 3)(DENG)
Designs and implements data pipelines and data stores to acquire and prepare data. Applies data engineering standards and tools to create and maintain data pipelines and data stores.
Testing (Level 3)(VISL)
Designs and conducts tests of the data visualisation to assure it meets the needs of end users, that data is succinct and that information maps to underlying raw data through known and appropriate translation and visual representation techniques. Corrects errors and retests to achieve an error-free result.
Data pipelines and stores (Level 2)(DENG)
Assists in developing and implementing data pipelines and data stores.
Automation and opportunities (Level 5)(VISL)
Maintains an awareness of current and emerging information analysis, formatting and visual aids and the relative value and challenge in using the different methods. In particular, to inclusion and accessibility to information.
Automation and opportunities (Level 4)(VISL)
Works with others to create automated scripts and processes that prepare the data ready for presentation. Works with job scheduling to ensure data preparation activities fit at the appropriate point of data acquisition and do not impact on other system resource needs e.g. backups.
Information requirements and search (Level 5)(BINT)
Evaluates the need for analytics, and assesses the problems to be solved and which internal or external data sources to use or acquire.
Testing (Level 4)(VISL)
Plans, designs and conducts tests of data visualisation to assure it meets the needs of end users, that data is succinct and that information maps to underlying raw data through known and appropriate translation and visual representation techniques. Corrects errors and retests to achieve an error-free result.
Process, methods and standards (Level 3)(FEDIP Data)
Develops data hypotheses and analysis methods. Trains and evaluates analytics models, sharing insights and findings, and continues to iterate with additional data for improvement.
Process, methods and standards (Level 4)(BINT)
Develops and applies processes to support the analysis needs of the organisation. Defines standard and non-standard techniques and tools to deliver data analysis such as OLAP reporting, data mining, predictive analysis and data storytelling.
Information requirements and search (Level 4)(BINT)
Determines what information is required and defines search and other criteria to meet a specified requirement.
Information requirements and search (Level 3)(BINT)
Determines what information is required and defines search and other criteria to meet a specified requirement.
Information requirements and search (Level 2)(BINT)
Assists in the establishment of information needs and the definition of search criteria to meet the requirements.
Management and leadership (DATM)(Level 6)
Takes overall responsibility for directing the operation of data management within the organisation and ensuring the provision of information that meets the business needs of the organisation.
Corporate data policy (DTAN)(Level 5)
Contributes to the development and maintenance of the corporate data management policy within the organisation.
Assurance of data structures and models (DTAN)(Level 5)
Manages the iteration, review and maintenance of data requirements and data models.
Data requirements documentation (DTAN)(Level 5)
Manages the investigation of corporate data requirements, documenting them according to the required standards utilising the prescribed methods and tools.
Advice and guidance (DTAN)(Level 5)
Sets standards for data modelling and design tools and techniques, advises on their application, and ensures compliance.