NCF Category: Data Science

Develops plans demonstrating how user needs will be met.

Identifies where structured User Research / User Centered Design can add value, drawing in colleagues from these professions to deliver in collaboration.

Ensures that reporting processes are robust, efficient and fit for purpose.

Advises persuasively on the available standards, procedures, methods, tools and techniques.

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

Contributes to the development of analytics policy, standards and guidelines.

Understands the context of analysis including the identification of stakeholders and appreciation of wider issues.

4

Sets direction and leads in establishing and managing analytical methods, techniques and capabilities.

Sets standards and guidelines for the application of a range of data science techniques to business problems and oversees their implementation.

Leads the expansion of data science techniques employed to take advantage of under/ exploited data.

Sets direction and leads the introduction and use of analytics to meet overall business requirements, ensuring consistency across all user groups.

Identifies, promotes and shares best practice.

Plans and leads strategic, large scale and complex data science initiatives to generate insights, create value and drive decision-making.

Develops analytics policy, standards and guidelines.

Provides authoritative expert advice on a wide range of analytical techniques.

Leads data science recruitment activity. 

Promotes and monitors continuous professional development of other staff.

Develops knowledge of unfamiliar techniques and shares knowledge.

Promotes the team’s reputation for professionalism.

Looks for ways to improve ways of working within current area of responsibility, suggesting novel uses of existing data and technology. 

Experiments with innovations, manages and learns from failures and shares lessons learned within the team.

Contributes ideas as part of team discussion when engaged in specific projects.

Looks for ways to automate and improve efficiency of repeatable analytical workflows.

Applies robust and ethical techniques in the transformation of data from one format or medium to another in line with organisational policies and procedures.

Uses data exploration techniques to help evaluate the characteristics of a dataset and its suitability for subsequent analysis.

Understands and assists in the development and modification of source data e.g. data pipelines, datasets, data stores and metadata in accordance with established processes.

Shares knowledge of data sources with colleagues.

Uses defined data modelling and design techniques under guidance.

Makes effective use of available data sources using appropriate methods to extract data for analysis in an ethical manner.

Creates new datasets through the manipulation of multiple data sources, including linking or matching data using techniques already established in the work area.

Recognises where external data sources can be integrated with own datasets.

Carries out routine data quality checks and remediation such as handling missing data or outliers and performing data cleansing.

Documents and communicates the details of data structures to others.

Performs administrative tasks to ensure accessibility, retrievability, security and protection of data.

Plans, designs, creates, amends, refactors, verifies, tests and documents simple to moderately complex programs/scripts.

Develops expertise in available tools and infrastructure and shares this with others.

Applies agreed standards, version control and tools, to achieve a well-engineered result.

Collaborates in reviews of work with others and is able to code with others using an agreed platform and versioning methodology such as git.

Seeks to maximise reusability and reproducibility of developed code and practices, such as Coding in the Open, and shares developments with colleagues.

Provides quality assurance of data science work using appropriate guidance and frameworks and takes account of ethical considerations.

Contributes to documentation to assure that appropriate quality control activities and ethics considerations have taken place.

Reports own analytical work in sufficient detail, presenting results in both written and oral form.

Identifies key messages from the work and translates these into terminology suitable for either technical or non-technical audiences.

Explains the evidence provided by own analysis and comments on the context and connections of interest to the customer of the analysis.

Clearly explains the implications of the analysis for the project / policies under examination or the impact on operational processes and/or research being undertaken.

Presents data and data science outputs through various visual techniques and provides clear narratives using appropriate language that meets customer needs.

Supports data preparation from existing sources.

Selects appropriate visualisation techniques and tools from the options available.

Engages with users directly and/or works with user interface designers to prototype and refine specified visualisations.

2

You apply a range of techniques to transform data into valid and purposeful information. Undertakes analysis and data science activities to deliver analytical outputs in accordance with customer needs and as tasked within the project team.

Ensures work conforms to agreed standards.

Seeks advice on the application of techniques when appropriate.

Analyses and reports findings and remedies simple issues using algorithms implemented in standard software frameworks and tools. 

Applies existing data science techniques to new problems and datasets using specialised programming techniques.

Evaluates and reports on the outcomes and performance of data science systems and models.

Actively identifies and takes opportunities to further own professional development.

Takes advantage of opportunities to share own knowledge / expertise.