NCF Category: Data Science

Applies a range of analytical techniques, in consultation with experts where appropriate, and with sensitivity to the limitations of the techniques.

Clearly articulates dependencies on other teams / systems / infrastructure and builds these in to plans.

Operationalises and automates activities for the efficient and timely production of data products eg reproducable analytical pipeline (rap).

Designs, implements, tests, and improves technical architectures and systems.

Manages reviews of the benefits and value of analytics techniques and tools and recommends improvements.

Communicates results using methods appropriate to the target audience, ensuring that model performance and uncertainty are understood.

Effectively implements analysis and reporting in areas where there is some complexity and ambiguity.

Understands and applies rules and guidelines specific to analytics in healthcare and anticipates risks and other implications of modelling.

Investigates the described problem and available datasets to assess the usefulness of data science solutions, undertaking discovery activity to inform these investigations.

Ensures that solutions balance the essential and desired requirements.

Plans, establishes and manages processes for regular and consistent access to, and independent validation of, external information from multiple sources.

Sets standards for data modelling and design for analysis and ensures compliance.

Provides guidance in the selection and use of database and data warehouse architectures, software, and facilities.

Contributes to organisational policies, standards, and guidelines for data engineering.

Influences colleagues in data engineering to create data warehouses designed to support the demands of business intelligence and data analytics.

Takes technical responsibility across all stages and iterations of development.

Plans and drives software construction activities.

Measures and monitors applications of project/team standards for software construction including security and reproducible analytical pipeline principles.

Adopts and adapts appropriate software development methods, tools and techniques.

Contributes to the development of organisational policies, standards, and guidelines for software development.

Influences partners to ensure dependencies are handled and opportunities to accelerate or enhance delivery through collaboration are taken.

Develops and maintains links with academia and industry.

Champions innovative data analytics within and across teams.

Applies knowledge of new and evolving technologies to decide which novel methods to apply to the most challenging problems.

Actively shares new insights/opportunities with others and takes advantage of professional networks and other resources to build awareness of current and emerging technology / techniques.

Encourages and motivates innovation communities, teams and individuals to share creative ideas and learn from failures. Actively seeks out examples of data innovations in other internal and external products and considers their appropriateness for reuse.

Decides which innovations are most suitable and drives the case forward to delivery.

Leads the introduction of techniques, methodologies and tools to meet business requirements.

Work with end-users and Subject Matter Experts to identify alternative solutions to improve efficiency and effectiveness through exploitation of new datasets, new data analysis tools, technology and/or automation.

Influences customers and other partners to engage in proof-of-concept work to prove the potential value of innovative approaches while understanding and managing any associated risks.

Co-ordinates the application of data design and modelling techniques, to establish, modify or maintain data pipelines, data structures, datasets, and metadata for diverse datatypes.

Uses expertise in data exploration techniques for diverse data types to lead analytical work of this type.

Devises and implements data management processes for analytics, incorporating quality, retrieval, and retention processes in accordance with a robust set of ethical principles.

Leads work to independently validate external information from multiple sources.

Identifies, acquires, and maximises the analytical potential of new datasets including novel and diverse datatypes and sources.

Maintains and improves quality of data exploration work by identifying best practice and setting standards.

Uses expertise in manipulating and creating new data sources through linking or matching multiple datasets, including assessing and enhancing the quality of data linking.

Manages quality assurance for areas of responsibility throughout project lifecycle, escalating to stakeholders and external experts wherever appropriate.

Identifies and responds to legal and ethical concerns arising within area of responsibility.

Plans, organises and conducts formal quality and ethics assessments of complex projects.

Identifies and evaluates non-compliance with quality and ethics standards, determines underlying reasons for non-compliance and takes necessary remedial action.

Identifies opportunities to improve organisational control mechanisms.

Produces well-written and technically sound project reports and provides constructive review and assurance of reports authored by others.

Communicates key messages to customers and translates research, analysis and results for a non-technical audience.

Has comprehensive knowledge of the strengths and limitations of analysis and the underlying data and is able to provide caveats in a constructive way.

Presents analytical work appropriately tailored to a range of internal and external audiences.

Provides overall control to ensure the appropriate use of data visualisation tools and techniques. Advises on the appropriate use of data visualisation for different purposes and contexts to satisfy requirements.

Engages with customers, shares findings and leads on debates that may influence decision making, inspiring the team to do similarly.

Leads on or supports the team in more complex analytical discussions with customers and colleagues.