4tasks in this job
34skills it uses
6tools named
The skills this job leans on most
- 1Reconciling finance subledgers and close recordsNeeded in 3 of 4 tasks
- 2Mapping entity results and eliminating intercompany balances in consolidationNeeded in 3 of 4 tasks
ToolsMicrosoft ExcelMicrosoft Power BIMicrosoft PowerPointOneStreamCCH TagetikServiceNowCaseware
All 4 tasks, where people get stuck and all 34 skills
Tasks
- Reconcile and substantiate balance sheet accounts at period close
- Test the design and operating effectiveness of a data-dependent control
- Consolidate entity results into group accounts and decide which entity data the group relies on
- Assure the data behind statutory and sustainability disclosures before sign-off
Where people get stuck
- Writing evidence-led findings and auditable recommendations with their limits
- Presenting and defending evidence-based recommendations to decision-makers
- Designing testable data controls
All skills
- Reconciling finance subledgers and close records
- Assessing data source credibility and fitness for a question
- Assessing the control and reliability of end-user calculation files
- Calculating and verifying KPIs against their specification
- Combining tables safely: cardinality, fan-out and conservation of totals
- Comparing periods consistently
- Designing and appraising samples
- Designing and validating digital analytics event measurement
- Designing testable data controls
- Diagnosing data quality exceptions
- Diagnosing misleading data visualisations
- Disclosing AI contribution to professional work
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Explaining control types, dependencies and compensating controls
- Explaining how business events flow into accounting records
- Giving specific developmental feedback on data and AI work
- Independently checking analytical conclusions and claims
- Interpreting financial statements and ratios for decisions
- Interpreting sustainability reporting standards and metric boundaries
- Investigating procurement spend leakage and duplicate commitments
- Judging the materiality of defects and deficiencies for the intended use
- Mapping proposed process changes and control impacts
- Monitoring and testing data control effectiveness
- Reading business metrics
- Reading data tables: rows, fields, types and units
- Reconciling conflicting reports
- Running sensitivity and break-even analysis on model assumptions
- Testing competing explanations with discriminating evidence
- Testing the completeness and accuracy of reports and data that controls rely on
- Tracing data lineage upstream and downstream
- Validating records by matching, recomputation and end-to-end tracing
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
Paths to start
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
Business Data Controls and Reconciliation
Design, test and operate controls and reconciliations.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Diagnostic Investigation and Root Cause Analysis
Resolve contradictory evidence and find, verify and prevent the causes of business and data anomalies.
- Modules
- 5 open
- Practice data
- Raket Parts
7tasks in this job
70skills it uses
7tools named
The skills this job leans on most
- 1Monitoring and testing data control effectivenessNeeded in 6 of 7 tasks
- 2Writing evidence-led findings and auditable recommendations with their limitsNeeded in 5 of 7 tasks
- 3Reconciling finance subledgers and close recordsNeeded in 5 of 7 tasks
- 4Presenting and defending evidence-based recommendations to decision-makersNeeded in 3 of 7 tasks
- 5Designing testable data controlsNeeded in 2 of 7 tasks
ToolsMicrosoft ExcelMicrosoft Power BIMicrosoft PowerPointOneStreamCCH TagetikServiceNow+ 1 more
All 7 tasks, where people get stuck and all 70 skills
Tasks
- Reconcile and substantiate balance sheet accounts at period close
- Prepare a periodic performance or risk report for a management or governance committee
- Test the design and operating effectiveness of a data-dependent control
- Consolidate entity results into group accounts and decide which entity data the group relies on
- Design data-dependent controls for a new or changed finance or people process, system or automation
- Assure the data behind statutory and sustainability disclosures before sign-off
- Configure, test and release a change to a business system of record under change control
Where people get stuck
- Testing changes to data services and business systems for business meaning and downstream impact
- Explaining control types, dependencies and compensating controls
All skills
- Designing testable data controls
- Monitoring and testing data control effectiveness
- Presenting and defending evidence-based recommendations to decision-makers
- Reconciling finance subledgers and close records
- Writing evidence-led findings and auditable recommendations with their limits
- Assessing change risk, collisions and go or no-go
- Assessing data source credibility and fitness for a question
- Assessing data-service continuity and recoverability
- Assessing the control and reliability of end-user calculation files
- Building decision-focused reports and dashboards
- Calculating and verifying KPIs against their specification
- Classifying AI uses against regulatory obligations
- Combining tables safely: cardinality, fan-out and conservation of totals
- Communicating quantified uncertainty
- Communicating sensitive or unwelcome analytical findings
- Comparing periods consistently
- Constructing clear and honest charts
- Coordinating accountable handoffs between teams
- Designing and appraising samples
- Designing and running evaluations of AI systems
- Designing and validating digital analytics event measurement
- Designing automated pipelines and processes that fail safely and recover
- Diagnosing data quality exceptions
- Diagnosing misleading data visualisations
- Disclosing AI contribution to professional work
- Enforcing and auditing data access
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Estimating quantities and differences with intervals
- Evaluating and improving chart accessibility
- Explaining control types, dependencies and compensating controls
- Explaining how business events flow into accounting records
- Explaining technical work to accountable non-specialists
- Facilitating evidence-led retrospectives and corrective actions
- Gating releases on evidence with rollback ready
- Giving specific developmental feedback on data and AI work
- Identifying and quantifying decision downside and exposure
- Identifying keys and testing referential integrity
- Independently checking analytical conclusions and claims
- Interpreting correlation without inferring cause
- Interpreting financial statements and ratios for decisions
- Interpreting policy scope and delegated authority limits
- Interpreting sustainability reporting standards and metric boundaries
- Investigating procurement spend leakage and duplicate commitments
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Judging whether uncertainty changes the decision
- Making accountable decisions under uncertainty
- Mapping proposed process changes and control impacts
- Preparing change records with impact assessment and rollback
- Rating risks against appetite and choosing proportionate treatment
- Reading business metrics
- Reading charts and dashboards correctly, including their state
- Reading data tables: rows, fields, types and units
- Recognising and resolving ethical conflicts in data and AI work
- Recognising misleading numerical claims
- Reconciling conflicting reports
- Repairing data defects reversibly under owner authority
- Revising prior decisions when evidence changes
- Running incident command: severity, timeline and status updates
- Running sensitivity and break-even analysis on model assumptions
- Selecting charts for evidence and decisions
- Testing changes to data services and business systems for business meaning and downstream impact
- Testing competing explanations with discriminating evidence
- Testing the completeness and accuracy of reports and data that controls rely on
- Tracing data lineage upstream and downstream
- Validating records by matching, recomputation and end-to-end tracing
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
- Writing verifiable requirements and acceptance criteria
Paths to start
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
Business Data Controls and Reconciliation
Design, test and operate controls and reconciliations.
- 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
5tasks in this job
73skills it uses
7tools named
The skills this job leans on most
- 1Monitoring and testing data control effectivenessNeeded in 5 of 5 tasks
- 2Reconciling finance subledgers and close recordsNeeded in 3 of 5 tasks
- 3Designing testable data controlsNeeded in 2 of 5 tasks
- 4Testing the completeness and accuracy of reports and data that controls rely onNeeded in 2 of 5 tasks
- 5Testing changes to data services and business systems for business meaning and downstream impactCore to this role
ToolsMicrosoft PowerPointMicrosoft Power BIMicrosoft ExcelOneStreamCCH TagetikServiceNow+ 1 more
All 5 tasks, where people get stuck and all 73 skills
Tasks
- Prepare a periodic performance or risk report for a management or governance committee
- Test the design and operating effectiveness of a data-dependent control
- Consolidate entity results into group accounts and decide which entity data the group relies on
- Design data-dependent controls for a new or changed finance or people process, system or automation
- Assure the data behind statutory and sustainability disclosures before sign-off
Where people get stuck
- Mapping entity results and eliminating intercompany balances in consolidation
- Interpreting sustainability reporting standards and metric boundaries
All skills
- Designing testable data controls
- Monitoring and testing data control effectiveness
- Reconciling finance subledgers and close records
- Testing changes to data services and business systems for business meaning and downstream impact
- Testing the completeness and accuracy of reports and data that controls rely on
- Assessing change risk, collisions and go or no-go
- Assessing data source credibility and fitness for a question
- Assessing data-service continuity and recoverability
- Assessing the control and reliability of end-user calculation files
- Building decision-focused reports and dashboards
- Calculating and verifying KPIs against their specification
- Classifying AI uses against regulatory obligations
- Combining tables safely: cardinality, fan-out and conservation of totals
- Communicating quantified uncertainty
- Communicating sensitive or unwelcome analytical findings
- Comparing periods consistently
- Constructing clear and honest charts
- Coordinating accountable handoffs between teams
- Designing and appraising samples
- Designing and running evaluations of AI systems
- Designing and validating digital analytics event measurement
- Designing automated pipelines and processes that fail safely and recover
- Diagnosing data quality exceptions
- Diagnosing misleading data visualisations
- Disclosing AI contribution to professional work
- Enforcing and auditing data access
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Estimating quantities and differences with intervals
- Evaluating and improving chart accessibility
- Explaining control types, dependencies and compensating controls
- Explaining how business events flow into accounting records
- Explaining technical work to accountable non-specialists
- Facilitating evidence-led retrospectives and corrective actions
- Facilitating group decisions using disputed evidence
- Gating releases on evidence with rollback ready
- Giving specific developmental feedback on data and AI work
- Identifying and quantifying decision downside and exposure
- Identifying keys and testing referential integrity
- Independently checking analytical conclusions and claims
- Interpreting correlation without inferring cause
- Interpreting financial statements and ratios for decisions
- Interpreting policy scope and delegated authority limits
- Interpreting sustainability reporting standards and metric boundaries
- Investigating procurement spend leakage and duplicate commitments
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Judging whether uncertainty changes the decision
- Making accountable decisions under uncertainty
- Mapping proposed process changes and control impacts
- Preparing change records with impact assessment and rollback
- Presenting and defending evidence-based recommendations to decision-makers
- Rating risks against appetite and choosing proportionate treatment
- Reading business metrics
- Reading charts and dashboards correctly, including their state
- Reading data tables: rows, fields, types and units
- Reasoning about systems, feedback and second-order effects
- Recognising and resolving ethical conflicts in data and AI work
- Recognising misleading numerical claims
- Reconciling conflicting reports
- Repairing data defects reversibly under owner authority
- Revising prior decisions when evidence changes
- Running incident command: severity, timeline and status updates
- Running sensitivity and break-even analysis on model assumptions
- Sampling and reviewing a team's work against standards
- Selecting charts for evidence and decisions
- Testing competing explanations with discriminating evidence
- Tracing data lineage upstream and downstream
- Validating records by matching, recomputation and end-to-end tracing
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
- Writing evidence-led findings and auditable recommendations with their limits
- Writing verifiable requirements and acceptance criteria
All tools
- Microsoft PowerPoint
- Microsoft Power BI
- Microsoft Excel
- OneStream
- CCH Tagetik
- ServiceNow
- Caseware
Paths to start
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
Business Data Controls and Reconciliation
Design, test and operate controls and reconciliations.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Diagnostic Investigation and Root Cause Analysis
Resolve contradictory evidence and find, verify and prevent the causes of business and data anomalies.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonAnalytics Engineering: Tested, Version-controlled Transformation
About the role
Accountable for the finance control framework and consolidated close across a group of entities. Heads the controllers of the entities rather than running one close. Data judgement sits in deciding which entity data and consolidation outputs the group accounts can rely on.
Also called Head of Financial Control