Explore Tasks
Assess continuity and third-party dependency risk for a data or AI service
The service owner receives a dependency map, impact assessment and continuity treatments for supplier or platform failure.
1job does it
3jobs help with it
41skills it needs
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
- Assessing data-service continuity and recoverability
- Classifying AI uses against regulatory obligations
- Judging whether and how to use AI for a task
- Evaluating fitness and full cost of AI-assisted work
- Analysing error patterns and failure modes in models and AI systems
- Monitoring model fitness and drift
- Evaluating responsible AI use risks
- Recognising personal data and privacy duties
- Assessing privacy risk through data protection impact assessments
- Recognising cybersecurity threats to data work
- Recognising and containing suspected personal data breaches
- Assessing data-driven fairness and bias
- Assessing supplier dependency, data-handling and exit risk
- Explaining control types, dependencies and compensating controls
- Rating risks against appetite and choosing proportionate treatment
- Exercising human oversight of automated and AI outputs
- Evaluating supplier total cost and value
- Investigating procurement spend leakage and duplicate commitments
- Writing verifiable requirements and acceptance criteria
- Comparing options against explicit decision criteria
- Interpreting supplier contract duties, terms and exposure
- Interpreting policy scope and delegated authority limits
- Gating releases on evidence with rollback ready
- Designing automated pipelines and processes that fail safely and recover
- Evaluating software architecture for data and AI systems
- Setting and reviewing reliability objectives and error budgets for data and AI services
- Monitoring data quality and freshness in production
- Recovering data pipelines safely
- Evaluating service performance and quality trade-offs
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
Responsible AI Governance and Assurance
Govern and assure AI across its lifecycle including third-party AI and redress.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Procurement, Spend and Supplier Analytics
Analyse spend, contract exposure and supplier value.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonData Product Reliability: Release Gates, Service Levels and IncidentsApplied AI at Work