Data and analytics – FEDIP Job Profiles

Stakeholder engagement (Level 5) (BINT)

Plans and manages clinical coding activities in line with stakeholder requirements. Ensures that clinical coding processes are robust efficient and fit for purpose.

Security and safeguards (Level 5) (BINT)

Establishes strategic approaches to safeguarding clinical coding data and any analysis results, looking ahead to new and innovative approaches to data security

Policies, standards, and guidelines (Level 5) (BINT)

Leads the development of clinical coding policy, standards and guidelines to meet the current and future needs of the organisation.

Policies, standards, and guidelines (Level 5) (BINT)

Leads the development of clinical coding policy, standards and guidelines to meet the current and future needs of the organisation.

Methods and techniques (Level 5) (BINT)

Champions the organisation’s commitment to efficient and effective clinical coding.

Process, methods and standards (Level 7) (AUDT)

Sets direction and leads the introduction and use of clinical coding processes, methods and standards to meet business requirements, ensuring consistency of application and service provision.

Review findings (Level 7) (AUDT)

Leads the process improvement function to assess process improvement opportunities and maximise benefit.

Review findings (Level 6) (AUDT)

Authorises the issue of formal reports to management on the effectiveness and efficiency of control mechanisms and the extent of compliance of systems with standards, regulations and/or legislation.

Function leadership (Level 6) (AUDT)

Ensures audit coverage is sufficient to provide the business with assurance of adequacy and integrity. Obtains and manages appropriate specialist expertise to contribute highly specialised technical knowledge and experience where required.

Audit strategy (Level 6) (AUDT)

Works with senior management to review the effectiveness of existing audit strategy and contributes to strategy revision and/or definition.

Audit standards (Level 6) (AUDT)

Develops organisational policies, standards, procedures and guidelines for the conduct of audits.

Audit roadmap (Level 6) (AUDT)

Leads the production of the audit roadmap.

Audit planning (Level 6) (AUDT)

Leads the planning and resourcing of audits and/or conformance reviews at organisation level, ensuring objectivity and impartiality of the audit process is rigorously applied.

Advice and guidance (Level 6) (AUDT)

Provides general and specific clinical coding advice to senior management on ways of improving the effectiveness and efficiency of control mechanisms.

Security and safeguards (Level 5) (BINT)

Ensures that all clinical coding activity complies with data and information security processes.

Policies, standards, and guidelines (Level 5) (BINT)

Manages the development of clinical coding policy, standards and guidelines to meet the current and future needs of the organisation.

Risk assessment (Level 5) (AUDT)

Leads risk assessments and risk reviews. Identifies and evaluates associated risks and how they can be mitigated.

Audit standards (Level 5) (AUDT)

Contributes to the development of new internal standards and updates to existing standards.

Audit roadmap (Level 5) (AUDT)

Contributes to the development of the audit roadmap.

Audit management (Level 5) (AUDT)

Ensures audits under own responsibility are managed, planned, resourced, and executed within roadmap timescales.

Advice and guidance (Level 5) (AUDT)

Provides general and specific audit advice to management on ways of improving the effectiveness and efficiency of control mechanisms.

Information requirements and search (Level 4) (BINT)

Determines what information is required, and defines search and other criteria to meet a specified requirement.

Analysis (Level Four) (BINT)

Undertakes analytical activities to deliver analysis outputs in accordance with service needs and conforming to agreed standards.

Sourcing and validation (Level Four) (BINT)

Investigates available internal and external information sources to establish what information is available. Identifies and establishes the reliability and data risks of external sources of information of relevance to the operational needs of the enterprise.

Security and safeguards (Level Four) (BINT)

Ensures that all clinical coding activity complies with data and information security processes.

Policies, standards, and guidelines (Level Four) (BINT)

Contributes to the development of local clinical coding policy, standards and guidelines.

Analysis (Level Four) (BINT)

Undertakes analytical activities to deliver analysis outputs, conforming to agreed standards.

Security and safeguards (Level Three) (BINT)

Applies appropriate security and quality safeguards to the handling of data, information, and any analysis results throughout the data lifecycle.

Analysis (Level Three) (BINT)

Undertakes basic analytical activities, and assists with more complex activities, to deliver analysis outputs that conform to agreed standards.

Sourcing and validation (Level Three) (BINT)

Investigates available information sources to establish what information is available. Assesses the integrity and reliability of data from identified sources.

Sourcing and validation (Level Two) (BINT) Copy

Assists in the investigation of available information sources to establish what information is available and the reliability of such information.

Security and safeguards (Level Two) (BINT)

Assists in the application of appropriate safeguards and security procedures to the handling of data and any analysis results.

Validation (DATM) (Level Five)

Independently validates external information from multiple sources.

Management and leadership (DATM) (Level Five)

May take responsibility for managing a team or contributing to the development of staff within an organisation. May be involved in scheduling staff activities and planning future data governance activities.

Data governance (DATM) (Level Five)

Defines and implements data governance processes, including classification, quality, retrieval and retention processes. Champions data ownership and stewardship to raise awareness of data and its value as a strategic asset.

Data structures (DATM) (Level Five)

Derives data governance structures and metadata to support consistency of information retrieval, combination, analysis, pattern recognition and interpretation, throughout the organisation.

Validation (DATM) (Level Four)

Assesses the integrity of data from multiple sources.

Data structures (DATM) (Level Four)

Enables the availability, integrity and searchability of information through the application of formal data and metadata structures and protection measures.

Data governance (DATM) (Level Four)

Understands the concept of managing data as an asset and the roles of data ownership and data stewardship. Provides support, advice and guidance on data governance good practice.

Validation (DATM) (Level Three)

Monitors and maintains data quality through regular reviews and validation checks.

Data structures (DATM) (Level Three)

Protects the availability, integrity and searchability of information through the application of formal data structures and protection measures.

Data governance (DATM) (Level Three)

Communicates the details of data governance procedures to others, helping their understanding and compliance.

Evaluation (Level Four) (MLNG)

Advises on the effectiveness of specific techniques, based on project findings and on knowledge of wider research. Assesses machine learning suitability and designs and develops machine learning solutions for a range of business problems.

Solutions (Level 5) (DAAN)

Leads the implementation of data analytics solutions.

Processes, tools and methods (Level 5) (DAAN)

Guides the selection and application of advanced analytical techniques.

Process and validate (Level 5) (DAAN)

Manages data analytics activities, establishing frameworks and methodologies aligned with business objectives and data governance policies.

Business needs (Level 5) (DAAN)

Translates business needs into analytics requirements and identifies data-driven solutions.

Policies (Level Five) (MLNG)

Contributes to the development of organisational policies for the creation, training and use of machine learning systems.

Evaluation (Level Five) (MLNG)

Architects end-to-end machine learning pipelines and systems. Evaluates and selects appropriate tools, frameworks, and infrastructure for machine learning projects.

Collaboration (Level Four) (MLNG)

Collaborates with cross-functional teams to integrate machine learning models into production systems. Conducts in-depth performance analysis and troubleshoots issues.

Collaboration (Level Five) (MLNG)

Collaborates with stakeholders to align machine learning initiatives with organisational goals.

Strategy (Level Six) (DAAN)

Develops organisational strategies and roadmaps for data analytics.

Process and validate (Level Six) (DAAN)

Oversees the delivery of analytics projects and programmes. Promotes the ethical use of data and data analytics.

Processes, tools and methods (Level Four) (DAAN)

Contributes to the development of data analytics processes and standards. Identifies opportunities for improving data analytics practices.

Data preparation (Level Four) (DAAN)

Cleans raw data by identifying and resolving duplicates, errors, extreme values, and other anomalies.

Data analysis (Level Four) (DAAN)

Conducts end-to-end data analysis, defining data requirements and ensuring data integrity.

Data preparation (Level Three) (DAAN)

Supports data analytics by gathering and preparing data from multiple sources.

Data analysis (Level Three) (DAAN)

Applies analytical and statistical methods and software tools to analyse data and develop reports.

Collaborate (Level Three) (DAAN)

Collaborates with team members to refine analysis techniques and ensure data quality.

Model evaluation and advice (Level Six)(DATS)

Leads the introduction and use of data science and analytics to drive innovation and business value.

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.