Sample resume reports

Sample reports

Real insights. De-identified.

Investment Banking — Graduate

Hong KongInvestment DivisionTarget: 1–2 pages

72%86%

✓ Matched (10)

Asset managementPortfolio managementInvestment analysisEquity & fixed incomeQuantitative analyticsMacro / economic researchClient coverage & advisoryPython / data pipelineCapital marketsAUM growth

Gaps to address (7)

Passive investing / ETF / index strategyRelative value analysisThought leadership / contentAI / digital innovationESG / sustainability lensBloomberg / FactSet / IG toolsRisk management language

STAR rewrites

3 shown · 7+ typically included in a full report

01 · Macro-Economic Research

Before

Refined and automated an existing data pipeline in R/Python, consolidating fragmented central bank policy rate, core CPI, and real GDP data across 25 economies.

After

Engineered an automated R/Python data pipeline consolidating central bank policy rates, core CPI and real GDP across 25 economies, eliminating manual data fragmentation and enabling cross-sectional OLS analysis that identified statistically significant relationships between policy rate shifts and inflation outcomes — insights directly applicable to macro-driven investment positioning.

Why it works — Connects the technical work explicitly to investment decision-making relevance, which is central to monitoring macro events and global economic trends.

02 · Portfolio Construction

Before

Co-developed asset allocation proposals for 5 client portfolios, assessing potential savings from proposed tax structures and preparing presentation decks.

After

Constructed risk-return asset allocation frameworks for 5 HNW client portfolios spanning equities, fixed income and alternative assets, evaluating structural tax efficiency and presenting tailored investment strategies to clients with eight-figure combined AUM.

Why it works — Repositioning the bullet around asset-class breadth and portfolio construction mirrors the day-to-day management of traditional asset class portfolios across the risk spectrum.

03 · AI-Driven Investment Analytics

Before

Constructed a decision-support pipeline where 3 LLM agents score 10 data center sites against 20+ weighted parameters, then deliberate up to 3 rounds.

After

Architected a multi-agent AI system deploying 3 specialised LLM agents to evaluate 18 capital-allocation targets across 20+ weighted parameters — infrastructure, financial and sustainability — simulating an investment committee deliberation process to surface risk-adjusted site selection recommendations.

Why it works — Framing this as an investment committee simulation with explicit AI and capital-allocation language satisfies the requirement for graduates with AI-related project exposure.

Coach note

3+ notes in a full report

Your quantitative pedigree is a genuine differentiator for this Hong Kong role — the division respects rigour, and your GPA, honours and advanced coursework should be called out explicitly in a two-line profile summary at the top. Name your target asset class (public markets, multi-asset) and lead with your language profile.

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