Help me prepare for my upcoming interview!
Hi all,
I’m a Data Scientist at a finance company preparing for a FAANG FP&A + Data role. While I work extensively with financial statements, this role emphasizes P&L forecasting, Long Range Planning (LRP), and AOP.
I really really need this job. I’d love to learn how professionals approach this in real-world settings:
P&L:
How do you forecast each P&L line given different drivers across 4–5 business units?
Do you use data science techniques (time series), or is it primarily driver-based modeling?
At what level do you forecast (line item, BU, or consolidated)?
Do you forecast bottom-up (BU to company) or top-down and allocate?
Scenario Analysis:
For key drivers, do you rely on Base/Bull/Bear scenarios or use more robust methods like Monte Carlo simulations?
If using scenarios, how do you decide which drivers to sensitize and by how much?
Other:
How do you forecast, especially LRP, with limited historical data (e.g., new products or markets)?
How do you incorporate and attribute macro variables (rates, inflation, FX) into forecasts?
How do you establish and maintain a single source of truth across business units, especially if their BU metrics are calculated differently from global metrics?
I was asked about variance analysis and forecasting approaches in the first round. What additional topics or case styles should I expect next?
I would appreciate any advice or insight I can get. Thank you!