Explore Tasks
Design and govern the operating model for data, analytics and AI work in a function
A function receives decision rights, roles, service model (central, hub-and-spoke), standards adoption and an exception process.
1job does it
19jobs help with it
37skills it needs
- Head of Data & Analytics
- Analytics Manager
- Head of Data Architecture
- Head of Data Governance
- Head of Privacy
- Director of Data & Analytics
- Chief Data & AI Officer
- Head of Engineering
- Engineering Director
- Chief Technology Officer
- Head of Finance
- Head of Procurement
- Finance Director
- Procurement Director
- Chief Financial Officer
- HR Director
- Head of Marketing
- Head of Sales
- Head of Operations
- Head of Insight
Does itHelps with it
- Reading and tracing unfamiliar code
- Reviewing human- and AI-generated code changes for correctness and risk
- Sampling and reviewing a team's work against standards
- Diagnosing misleading data visualisations
- Verifying reports and dashboards before and after release
- Verifying AI-assisted outputs against sources
- Disclosing AI contribution to professional work
- Testing competing explanations with discriminating evidence
- Independently checking analytical conclusions and claims
- Escalating unresolved risks with evidence and clear ownership
- Giving specific developmental feedback on data and AI work
- Judging the materiality of defects and deficiencies for the intended use
- Classifying AI uses against regulatory obligations
- Governing shared data definitions
- Enforcing and auditing data access
- Judging whether and how to use AI for a task
- Applying data classification and handling rules
- Assigning and operating data ownership and stewardship
- Designing enforceable data governance policies
- Mapping stakeholders' decisions, constraints and needs
- Working through stakeholder conflict over evidence and responsibility
- Identifying and prioritising critical data elements
- Designing decision rights and dispute routes for data and AI work
- Building data protection by design into data products and pipelines
- Designing and comparing decision scenarios
- Writing evidence-led findings and auditable recommendations with their limits
- Communicating quantified uncertainty
- Presenting and defending evidence-based recommendations to decision-makers
- Testing investment business cases under uncertainty
- Identifying and quantifying decision downside and exposure
- Prioritising work by evidenced value, cost, risk and confidence
- Eliciting the decision behind an analytical request
- Judging whether external evidence applies to the decision context
- Comparing options against explicit decision criteria
- Making accountable decisions under uncertainty
- Reasoning about systems, feedback and second-order effects
- Appraising options on a common incremental basis against a do-nothing baseline
Paths that teach the skills it needs
Skill Path
Data Literacy for Business Decisions
Judge whether a business claim from a table, KPI, chart or dashboard really holds up.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Data Governance, Catalogues and Lineage
Govern definitions, stewardship, lineage and enforceable policy.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Evidence-based Briefing and Influence
Brief and influence accountable decision-makers with evidence, its limits and unwelcome findings, and check the message landed.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonFinancial Modelling and Decision SupportApplied AI at Work