8tasks in this job
65skills it uses
8tools named
The skills this job leans on most
- 1Reconciling finance subledgers and close recordsNeeded in 6 of 8 tasks
- 2Analysing costs, allocation and margin driversNeeded in 5 of 8 tasks
- 3Explaining how business events flow into accounting recordsNeeded in 4 of 8 tasks
- 4Interpreting budgets and planning assumptionsNeeded in 1 of 8 tasks
- 5Testing the completeness and accuracy of reports and data that controls rely onCore to this role
ToolsMicrosoft ExcelSAP S/4HANAOracle Hyperion and Oracle EPM Cloud (Planning, HFM, FCCS, EPBCS)Microsoft Power BIOneStreamCasewareFortnoxMicrosoft Dynamics 365 Finance and Operations
All 8 tasks, where people get stuck and all 65 skills
Tasks
- Reconcile and substantiate balance sheet accounts at period close
- Reconcile payroll to finance postings
- Produce an accountable operating budget
- Evaluate receivables exposure and prioritise authorised collection action
- 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
- Verify supplier master data and bank detail changes against fraud controls
- Assess expected credit loss and recommend the bad debt provision
Where people get stuck
- Testing changes to data services and business systems for business meaning and downstream impact
- Designing testable data controls
- Interpreting financial statements and ratios for decisions
All skills
- Analysing costs, allocation and margin drivers
- Explaining how business events flow into accounting records
- Interpreting budgets and planning assumptions
- Reconciling finance subledgers and close records
- Analysing business drivers and contributions
- Analysing pay equity with raw and adjusted pay gaps
- Analysing working-capital drivers and cash conversion
- Assessing customer creditworthiness and setting limits
- Assessing data source credibility and fitness for a question
- Assessing the control and reliability of end-user calculation files
- Assigning and operating data ownership and stewardship
- Building driver-based financial forecasts
- Calculating and verifying KPIs against their specification
- Combining tables safely: cardinality, fan-out and conservation of totals
- Communicating quantified uncertainty
- Comparing periods consistently
- Constructing a controlled cash-flow plan
- Designing and comparing decision scenarios
- Designing and validating digital analytics event measurement
- Designing auditable decision models
- Designing efficient and reproducible investigations
- Diagnosing data quality exceptions
- Diagnosing duplicate records
- Diagnosing forecast accuracy and bias and comparing methods fairly
- Diagnosing misleading data visualisations
- Diagnosing operational handoffs and flow
- Disclosing AI contribution to professional work
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Estimating accruals, provisions and expected credit loss under accounting policy
- Forecasting business trends and turning points for planning
- Giving specific developmental feedback on data and AI work
- Identifying and quantifying decision downside and exposure
- Independently checking analytical conclusions and claims
- Interpreting averages, weighted measures and mix effects
- Interpreting financial statements and ratios for decisions
- Interpreting policy scope and delegated authority limits
- Interpreting sustainability reporting standards and metric boundaries
- Interpreting trends and seasonality
- Interpreting workforce metrics and populations
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- Judging the materiality of defects and deficiencies for the intended use
- Making accountable decisions under uncertainty
- Mapping entity results and eliminating intercompany balances in consolidation
- Monitoring and testing data control effectiveness
- Presenting and defending evidence-based recommendations to decision-makers
- Prioritising collection actions from aged debt
- Rating risks against appetite and choosing proportionate treatment
- Reading business metrics
- Reading data tables: rows, fields, types and units
- Recognising statutory incident reporting duties and deadlines
- Reconciling conflicting reports
- Repairing data defects reversibly under owner authority
- Resolving and escalating pay, incentive and payment exceptions within authority
- Running sensitivity and break-even analysis on model assumptions
- Testing competing explanations with discriminating evidence
- Testing investment business cases under uncertainty
- Tracing data lineage upstream and downstream
- Validating records by matching, recomputation and end-to-end tracing
- Variance analysis
- Verifying AI-assisted outputs against sources
- Verifying payment and bank-detail changes against fraud controls
- Verifying reports and dashboards before and after release
- Writing evidence-led findings and auditable recommendations with their limits
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
Coming soonFinancial Modelling and Decision Support
15tasks in this job
108skills it uses
10tools named
The skills this job leans on most
- 1Analysing costs, allocation and margin driversNeeded in 6 of 15 tasks
- 2Interpreting financial statements and ratios for decisionsNeeded in 5 of 15 tasks
- 3Designing testable data controlsNeeded in 2 of 15 tasks
- 4Testing changes to data services and business systems for business meaning and downstream impactNeeded in 1 of 15 tasks
- 5Interpreting budgets and planning assumptionsNeeded in 1 of 15 tasks
ToolsSAP S/4HANAPower QueryOracle Hyperion and Oracle EPM Cloud (Planning, HFM, FCCS, EPBCS)Microsoft ExcelFortnoxOracle NetSuite+ 4 more
All 15 tasks, where people get stuck and all 108 skills
Tasks
- Reconcile and substantiate balance sheet accounts at period close
- Reconcile payroll to finance postings
- Produce an accountable operating budget
- Evaluate receivables exposure and prioritise authorised collection action
- Test the design and operating effectiveness of a data-dependent control
- Define master data match and survivorship rules and recommend golden-record changes for the data owner's approval
- Verify a supplier payment run before release
- Set and review cost allocation rules and costing methods
- 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
- Oversee an automated or AI system in operational use and correct, restrict or withdraw faulty outputs
- Verify supplier master data and bank detail changes against fraud controls
- Assess expected credit loss and recommend the bad debt provision
Where people get stuck
- Setting and reviewing action thresholds for scores and model predictions
- Monitoring and testing data control effectiveness
- Escalating unresolved risks with evidence and clear ownership
All skills
- Analysing costs, allocation and margin drivers
- Designing testable data controls
- Interpreting budgets and planning assumptions
- Interpreting financial statements and ratios for decisions
- Testing changes to data services and business systems for business meaning and downstream impact
- Analysing business drivers and contributions
- Analysing error patterns and failure modes in models and AI systems
- Analysing pay equity with raw and adjusted pay gaps
- Analysing working-capital drivers and cash conversion
- Applying data classification and handling rules
- Assessing change risk, collisions and go or no-go
- Assessing customer creditworthiness and setting limits
- Assessing data source credibility and fitness for a question
- Assessing data-driven fairness and bias
- Assessing data-service continuity and recoverability
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Assessing privacy risk through data protection impact assessments
- Assessing supplier dependency, data-handling and exit risk
- Assessing the control and reliability of end-user calculation files
- Assigning and operating data ownership and stewardship
- Building driver-based financial forecasts
- 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
- Comparing periods consistently
- Constructing a controlled cash-flow plan
- Coordinating accountable handoffs between teams
- Designing and appraising samples
- Designing and comparing decision scenarios
- Designing and validating digital analytics event measurement
- Designing and versioning data contracts for consumers
- Designing auditable decision models
- Designing automated pipelines and processes that fail safely and recover
- Designing efficient and reproducible investigations
- Designing enforceable data governance policies
- Diagnosing data quality exceptions
- Diagnosing duplicate records
- Diagnosing forecast accuracy and bias and comparing methods fairly
- Diagnosing misleading data visualisations
- Diagnosing operational handoffs and flow
- 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 accruals, provisions and expected credit loss under accounting policy
- Evaluating fitness and full cost of AI-assisted work
- Evaluating responsible AI use risks
- Exercising human oversight of automated and AI outputs
- 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
- Forecasting business trends and turning points for planning
- Gating releases on evidence with rollback ready
- Giving specific developmental feedback on data and AI work
- Governing shared data definitions
- Identifying and quantifying decision downside and exposure
- Identifying keys and testing referential integrity
- Independently checking analytical conclusions and claims
- Influencing change without formal authority
- Interpreting averages, weighted measures and mix effects
- Interpreting policy scope and delegated authority limits
- Interpreting sustainability reporting standards and metric boundaries
- Interpreting trends and seasonality
- Interpreting workforce metrics and populations
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether and how to use AI for a task
- Making accountable decisions under uncertainty
- Managing master data identities and exceptions
- Mapping entity results and eliminating intercompany balances in consolidation
- Mapping proposed process changes and control impacts
- Monitoring and testing data control effectiveness
- Monitoring data quality and freshness in production
- Monitoring model fitness and drift
- Preparing change records with impact assessment and rollback
- Presenting and defending evidence-based recommendations to decision-makers
- Prioritising collection actions from aged debt
- Profiling data
- Rating risks against appetite and choosing proportionate treatment
- Reading business metrics
- Reading data tables: rows, fields, types and units
- Recognising and containing suspected personal data breaches
- Recognising cybersecurity threats to data work
- Recognising personal data and privacy duties
- Recognising statutory incident reporting duties and deadlines
- Reconciling conflicting reports
- Reconciling finance subledgers and close records
- Repairing data defects reversibly under owner authority
- Resolving and escalating pay, incentive and payment exceptions within authority
- Running incident command: severity, timeline and status updates
- Running sensitivity and break-even analysis on model assumptions
- Specifying AI transparency and explanation duties to affected people
- Standardising and cleaning data under agreed rules
- Testing competing explanations with discriminating evidence
- Testing investment business cases under uncertainty
- 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
- Variance analysis
- Verifying AI-assisted outputs against sources
- Verifying payment and bank-detail changes against fraud controls
- Verifying reports and dashboards before and after release
- Writing data quality rules
- Writing evidence-led findings and auditable recommendations with their limits
- Writing verifiable requirements and acceptance criteria
All tools
- SAP S/4HANA
- Power Query
- Oracle Hyperion and Oracle EPM Cloud (Planning, HFM, FCCS, EPBCS)
- Microsoft Excel
- Fortnox
- Oracle NetSuite
- OneStream
- Microsoft Dynamics 365 Finance and Operations
- Caseware
- ServiceNow
Paths to start
Skill Path
Data Preparation: Cleaning, Repair and Reconciliation
Check whether a table is fit for the job, then clean, repair and reconcile it with the evidence to back it.
- Modules
- 5 open
- Practice data
- Raket Parts
Tool Path
Excel for Analysis and Decision Models
Build and check Excel workbooks others can trust.
- Modules
- 5 open
- Runs in
- Your browser
Skill Path
Business Data Controls and Reconciliation
Design, test and operate controls and reconciliations.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonFinancial Modelling and Decision Support
13tasks in this job
110skills it uses
10tools named
The skills this job leans on most
- 1Reconciling finance subledgers and close recordsNeeded in 7 of 13 tasks
- 2Monitoring and testing data control effectivenessNeeded in 5 of 13 tasks
- 3Setting and reviewing action thresholds for scores and model predictionsNeeded in 2 of 13 tasks
- 4Designing testable data controlsNeeded in 2 of 13 tasks
- 5Testing changes to data services and business systems for business meaning and downstream impactNeeded in 1 of 13 tasks
ToolsSAP S/4HANAOracle Hyperion and Oracle EPM Cloud (Planning, HFM, FCCS, EPBCS)Microsoft ExcelPower QueryOneStreamServiceNow+ 4 more
All 13 tasks, where people get stuck and all 110 skills
Tasks
- Reconcile and substantiate balance sheet accounts at period close
- Produce an accountable operating budget
- Evaluate receivables exposure and prioritise authorised collection action
- Test the design and operating effectiveness of a data-dependent control
- Define master data match and survivorship rules and recommend golden-record changes for the data owner's approval
- Set and review cost allocation rules and costing methods
- 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
- Oversee an automated or AI system in operational use and correct, restrict or withdraw faulty outputs
- Verify supplier master data and bank detail changes against fraud controls
- Assess expected credit loss and recommend the bad debt provision
Where people get stuck
- Setting and reviewing action thresholds for scores and model predictions
- Escalating unresolved risks with evidence and clear ownership
- Exercising human oversight of automated and AI outputs
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
- Analysing business drivers and contributions
- Analysing costs, allocation and margin drivers
- Analysing error patterns and failure modes in models and AI systems
- Analysing pay equity with raw and adjusted pay gaps
- Analysing working-capital drivers and cash conversion
- Applying data classification and handling rules
- Assessing change risk, collisions and go or no-go
- Assessing customer creditworthiness and setting limits
- Assessing data source credibility and fitness for a question
- Assessing data-driven fairness and bias
- Assessing data-service continuity and recoverability
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Assessing privacy risk through data protection impact assessments
- Assessing supplier dependency, data-handling and exit risk
- Assessing the control and reliability of end-user calculation files
- Assigning and operating data ownership and stewardship
- Building driver-based financial forecasts
- 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
- Comparing periods consistently
- Constructing a controlled cash-flow plan
- Coordinating accountable handoffs between teams
- Designing and appraising samples
- Designing and comparing decision scenarios
- Designing and running evaluations of AI systems
- Designing and validating digital analytics event measurement
- Designing and versioning data contracts for consumers
- Designing auditable decision models
- Designing automated pipelines and processes that fail safely and recover
- Designing efficient and reproducible investigations
- Designing enforceable data governance policies
- Diagnosing data quality exceptions
- Diagnosing duplicate records
- Diagnosing forecast accuracy and bias and comparing methods fairly
- Diagnosing misleading data visualisations
- Diagnosing operational handoffs and flow
- 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 accruals, provisions and expected credit loss under accounting policy
- Evaluating fitness and full cost of AI-assisted work
- Evaluating responsible AI use risks
- Exercising human oversight of automated and AI outputs
- 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
- Forecasting business trends and turning points for planning
- Gating releases on evidence with rollback ready
- Giving specific developmental feedback on data and AI work
- Governing shared data definitions
- Identifying and quantifying decision downside and exposure
- Identifying keys and testing referential integrity
- Independently checking analytical conclusions and claims
- Influencing change without formal authority
- Interpreting averages, weighted measures and mix effects
- Interpreting budgets and planning assumptions
- Interpreting financial statements and ratios for decisions
- Interpreting policy scope and delegated authority limits
- Interpreting sustainability reporting standards and metric boundaries
- Interpreting trends and seasonality
- Interpreting workforce metrics and populations
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether and how to use AI for a task
- Making accountable decisions under uncertainty
- Managing master data identities and exceptions
- Mapping entity results and eliminating intercompany balances in consolidation
- Mapping proposed process changes and control impacts
- Monitoring data quality and freshness in production
- Monitoring model fitness and drift
- Preparing change records with impact assessment and rollback
- Presenting and defending evidence-based recommendations to decision-makers
- Prioritising collection actions from aged debt
- Profiling data
- Rating risks against appetite and choosing proportionate treatment
- Reading business metrics
- Reading data tables: rows, fields, types and units
- Recognising and containing suspected personal data breaches
- Recognising cybersecurity threats to data work
- Recognising personal data and privacy duties
- Recognising statutory incident reporting duties and deadlines
- Reconciling conflicting reports
- Repairing data defects reversibly under owner authority
- Resolving and escalating pay, incentive and payment exceptions within authority
- 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
- Specifying AI transparency and explanation duties to affected people
- Standardising and cleaning data under agreed rules
- Testing competing explanations with discriminating evidence
- Testing investment business cases under uncertainty
- 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
- Variance analysis
- Verifying AI-assisted outputs against sources
- Verifying payment and bank-detail changes against fraud controls
- Verifying reports and dashboards before and after release
- Writing data quality rules
- Writing evidence-led findings and auditable recommendations with their limits
- Writing verifiable requirements and acceptance criteria
All tools
- SAP S/4HANA
- Oracle Hyperion and Oracle EPM Cloud (Planning, HFM, FCCS, EPBCS)
- Microsoft Excel
- Power Query
- OneStream
- ServiceNow
- Microsoft Power BI
- Caseware
- Fortnox
- Microsoft Dynamics 365 Finance and Operations
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
Data Preparation: Cleaning, Repair and Reconciliation
Check whether a table is fit for the job, then clean, repair and reconcile it with the evidence to back it.
- Modules
- 5 open
- Practice data
- Raket Parts
Tool Path
Excel for Analysis and Decision Models
Build and check Excel workbooks others can trust.
- Modules
- 5 open
- Runs in
- Your browser
About the role
Accountable for close integrity, accounting controls, operating budgets and receivables-exposure decisions for an entity or business. Manages the accounting team and decides how controls are designed and which exceptions are accepted. Data judgement sits in deciding which ledger and system outputs the close can rely on.
Also called Finance Manager