While interning at a boutique PE firm, we were evaluating a mid‑market manufacturing target.

I was tasked with building a full‑stack DCF model to assess the target’s intrinsic value and support the investment memo.

I gathered historical financials, projected cash flows for five years, calculated free cash flow, selected an appropriate WACC based on comparable firms, applied a terminal growth rate, and performed sensitivity analysis on key assumptions. I documented each step in a clean Excel workbook and created visual dashboards for the partners.

The model indicated an enterprise value 12% below the asking price, which helped the team negotiate a favorable purchase price and ultimately contributed to a successful acquisition that generated a 15% IRR over three years.

During my role as a research analyst at a financial advisory firm, I was responsible for generating deal pipelines for the private equity team.

Identify emerging trends and sectors with attractive entry points for investment.

I subscribed to industry newsletters, monitored M&A databases, attended sector conferences, and built a weekly dashboard tracking revenue growth, M&A activity, and regulatory changes. I also conducted Porter’s Five Forces analyses for top‑performing sub‑sectors and shared concise briefs with the deal team.

The systematic approach surfaced three high‑growth fintech sub‑sectors, leading to two deal opportunities that progressed to term sheet stage within six months.

I was part of a two‑person team conducting due diligence on a SaaS company valued at $200 M.

Lead the financial due diligence, identify any red flags, and communicate findings to senior partners.

I built a detailed revenue quality model, reconciled GAAP and non‑GAAP metrics, and coordinated with the target’s CFO to obtain granular data. I uncovered a discrepancy in churn assumptions, escalated it to the partners, and worked with the target to adjust the forecast. I also prepared a risk‑adjusted valuation summary and presented it in a joint meeting with legal and operational teams.

The revised model reduced the purchase price by $12 M and incorporated earn‑out provisions tied to post‑close revenue targets, ultimately protecting the firm’s upside while securing the deal.

Our firm received three inbound deal teasers within a single week, each with potential upside but limited analyst bandwidth.

Create a prioritization framework to allocate resources efficiently and ensure high‑impact opportunities receive attention first.

I developed a scoring matrix based on deal size, strategic fit, expected IRR, and data availability. I ran quick preliminary valuations for each and presented the scores to the senior team. I then allocated analyst hours proportionally, focusing deep‑dive work on the top‑scoring deal while maintaining a high‑level review of the others.

The framework enabled us to close the highest‑scoring deal within the deadline, achieving a 20% IRR, while the other two deals were either passed on or scheduled for later review, optimizing team productivity.