FP&A, unit economics, and forecasting.
A 13 week cash forecast built to answer two decisions together: whether to hire and whether to raise. Weekly inflows and outflows drive runway, the lowest cash point, and the month cash turns negative, with scenario assumptions and a sensitivity grid across all four combinations.
A project and company finance model built for a music and creative business, covering revenue streams, cost tracking, a debt schedule, P&L, KPIs, dashboard structure, budget vs actual, ROI, runway, and debt progress.
client work, holds client data
A monthly business review model for direct to consumer brands, building orders from paid and organic funnels, splitting new from repeat revenue, and reporting contribution margin before and after marketing. Carries an inventory engine with reorder points and stockout flags, a monthly cash flow with runway, and a scenario switch.
The MBR Command Center reads this model.
A DeFi protocol FP&A model covering treasury, runway, protocol revenue, fees, token emissions, the insurance fund, sustainability metrics, and scenarios.
client work, holds client data
An income and expense tracker with Google Forms input, dashboards, KPIs, category analysis, savings rate, cash runway, charts, protected sheets, and a client-facing dashboard.
client work, holds client data
A 48 month model for commission based marketplaces with separate buyer and seller acquisition builds, each with its own channels, CAC and LTV. Produces a monthly P&L and balance sheet, buyer and seller cohort retention, a KPI sheet with profitability and cash runway, and scenario switching. Driven entirely from Inputs, no hardcodes.
A budget and forecast model built for a lending business, covering disbursements, interest income, late fees, processing fees, provisions, marketing CAC, collections, Opex, and profitability.
client work, holds client data
A SaaS operating model with four acquisition funnels each driving their own CAC, a three tier customer movement engine feeding an MRR and ARR waterfall, a headcount and salary build, an income statement to EBITDA, CAC payback on gross margin and ASC bases, burn, runway and profitability, and a three state model switch with sensitivity overrides across the assumptions.
A Python analysis comparing Tesla and NVIDIA from 2020 to 2025, covering annualised returns, volatility, Sharpe ratio, drawdowns, rolling and yearly returns, a risk-return comparison chart, and a simulation of how a 10,000 dollar investment in each and in a 50/50 split would have grown.
questions about any of this? email me.