At a Glance
- Tasks: Review and QA AI-agent rollouts in Financial Forecaster, ensuring accuracy and realism.
- Company: Join a leading financial services firm focused on innovation and excellence.
- Benefits: Attractive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic team environment with opportunities to enhance your skills and career.
- Why this job: Make a real impact in financial forecasting and reporting while working with cutting-edge technology.
- Qualifications: 5+ years in FP&A or related fields, with hands-on experience in Financial Forecaster.
The predicted salary is between 44595 - 54505 Β£ per year.
To qualify you must use Financial Forecaster regularly, weekly or more, as a working part of your job, with 5+ years of professional FP&A experience as an FP&A analyst/manager, financial reporting or technical accounting analyst, lender-reporting or treasury analyst, or controller.
Financial Forecaster knowledge we require:
- Working the model
- Multidimensional models: navigating models, dimensions and account hierarchies, and reading a cube slice at an exact coordinate rather than at whatever grain the UI lands on
- Scenarios: creating one, setting its parent, knowing what it inherits versus holds in its own cells, and locking it β plus identifying the forecast of record by its lock or acceptance date
- Accounts and assumptions: telling an input account from a calculated one, and knowing when to fix a figure by editing the account formula versus overriding an assumption cell
- CSV imports: loading actuals and driver data, and the unit and scale discipline an import demands
- Note surfaces: scenario notes, driver notes, policy notes, planning notes, assumption change logs and variance commentary
- Knowing what Financial Forecaster cannot do, so you can recognize a task that asks for a figure or a dimension member the model will never produce
Reading models & packs:
- Reading a scenario fluently: what is an input versus a calculated account, which cells are overridden, what a scenario inherits from its parent versus holds itself
- Reading a reporting pack against the model behind it: tracing a printed figure back to the account, scenario and coordinate it came from
- Recognizing the vintage that governs: which scenario is the forecast of record, when it was locked or accepted
- Decoding a coordinate (Time, Entity, Department, Product/Product Line, Region, and facility dimensions like Debtor or Aging Bucket)
- Finding & tying out the number
- Navigating account hierarchies and scenario trees to locate the figure that actually drives a covenant, a KPI, or a disclosure
- Unit and scale traps: thousands-versus-dollars mismatches, a cost base that cannot be reconciled to its own revenue
- Reconciling two in-world sources that disagree, and judging which one governs
Entity structure & governing documents:
- The reporting landscape: legal entity versus department versus segment versus consolidated
- Credit agreement mechanics: the provision fixing the accounting basis, Test Periods and test dates, fixed charge coverage and total net leverage
- Case relationships in the financial sense: parent and child scenarios, consolidated versus entity results
Measure types & classification:
- GAAP versus non-GAAP versus covenant measures
- Non-GAAP discipline: exclusions requiring a written determination that an amount is not normal and recurring
- Forecast versus projection under the AICPA PFI guidance
- The standards that decide the answer: going concern and the look-forward window, operating segments and the CODM
Documents, records & workflow:
- Document types: compliance certificate, borrowing base certificate, lender package, board or committee pre-read, earnings release and reconciliation
- What a finished deliverable requires versus what merely describes it
- App workflow surfaces: scenario creation and locking, saved views, and exports for large result sets
What you'll do:
- Review and QA AI-agent rollouts: work through completed agent runs in Financial Forecaster and judge whether the agent's answer is correct against the actual model and documents
- Identify failure modes: pinpoint where and why an agent succeeds too easily or fails wrongly
- Improve realism and difficulty: refine the task prompt and the seeded world so tasks reflect authentic FP&A and lender-reporting work
- Update grading guidance for accuracy: sharpen how answers are graded so correct answers pass and wrong ones fail
- Catch plausible-but-wrong answers that a non-expert reviewer would let slide
Requirements:
- Frequent hands-on Financial Forecaster use for real forecasting, covenant or reporting work in your current or recent role, weekly or more
- 5+ years in FP&A, financial reporting, technical accounting, or lender reporting
- Can read a Financial Forecaster model on sight
- Reflexive with Financial Forecaster's scenario and import mechanics
- Sound judgment on what a correct, complete answer looks like
Bonus: credit agreement compliance and borrowing base reporting; going concern or impairment analysis; segment reporting; SEC reporting or disclosure committee experience; hands-on experience across multiple models and entities.
FP&A Expert - Financial Forecaster employer: Mercor
Mercor is an exceptional employer that champions innovation and creativity in the AI sector, offering a fully remote work environment that promotes flexibility and independence. With a strong focus on employee growth, team members are encouraged to take ownership of their projects while benefiting from a supportive culture that values collaboration and continuous learning. Joining Mercor means being part of a forward-thinking company backed by industry leaders, where your contributions directly impact cutting-edge search technologies.