Role profile library Predefined role profile

Data analysts

The behaviours this profile measures, drawn from the great{with}talent job library and occupational research. Download the full competency-based interview guide to assess them.

Universal Competency Model
The full interview guideCompetency-based questions, follow-up probes and a 1–5 rating form for each behaviour — ready to print or run on screen.
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Behaviours assessed — 5 priority competencies
1

Analytical Skills

Breaks a problem down into its core elements. Draws on different data sources to inform their thinking, identifying the most pertinent issues within this. Incorporates the emotive elements of a situation into their thinking, before making sound inferences based on the available information.
Why this matters for Data analysts: The Skills England Data Analyst Apprenticeship Standard L4 names 'logical and methodical' as a core behaviour, statistical methods as core knowledge, and 'identify patterns and trends' as a core skill. Analytical reasoning across data sources is the entire purpose of the role.
2

Technical Capability

Has the necessary knowledge, skills and proficiency to conduct their role. Demonstrates mastery in their area of technical capability. Stays up to date with advances in their field and commits to their continuous development.
Why this matters for Data analysts: The Standard's knowledge covers tools (SQL, R/Python, Excel), data visualisation, and data architecture. SFIA Data Analytics (DTAN) and DDaT Data Analyst capability frameworks add depth. The technical floor is high and the toolset evolves continuously.
3

Influencing and Persuading

Presents simple, impactful messages in a compelling manner. Changes their emphasis and approach to address resistance, focusing on the value their ideas will bring different stakeholders. Confidently negotiates effective outcomes.
Why this matters for Data analysts: The Standard's skills include 'communicate findings to non-technical audiences'; DDaT Data Analyst expectations include 'communicates analysis'. The whole point of the analysis is to drive action — that is Influencing & Persuading. Argument from data is sustained and consequential.
4

Collaborative Working

Looks to understand others’ perspectives and objectives. Respects different styles/approaches, whilst adapting their own style to enable them to work effectively with others.
Why this matters for Data analysts: The Standard's skills include 'collaborate with stakeholders to define requirements'; DDaT requires 'works inclusively' and 'manages stakeholders'. Data analysts sit between business questions and technical methods; coordination across both is core.
5

Dependability

Conscientious and thorough in their approach to work, delivering what they promise to the necessary standard. Behaves in line with the organisation’s values and ethical principles.
Why this matters for Data analysts: The Standard's named behaviours 'thorough', 'takes responsibility' and 'professional', combined with data ethics and GDPR compliance and data quality requirements. The integrity of the data product depends on the analyst's reliability.