Jing Gao

Strategic Unit Economics & Financial Modelling:

• Developed granular unit economic models to dissect cost structures and profitability across complex supply chains, simulating the financial impact of operational changes, which skills directly transferable to modelling AI compute costs and infrastructure burn rates.
• Designed and executed a cost allocation framework distinguishing fixed, variable, and semi-variable elements to identify efficiency gaps, demonstrating the analytical rigour required to assess data centre and hardware economics.

Competitive Intelligence & Market Strategy:

• Led market strategy workstreams to redesign pricing structures, synthesizing external competitor benchmarks and elasticity data to drive revenue optimization; successfully identified margin leakage and forecasted the impact of commercial pivots.
• Conducted commercial due diligence and deal sourcing analysis, translating fragmented market data into high-impact investment theses and one-pagers for senior leadership, mirroring the M&A and partnership support responsibilities of the Technical Intelligence role.

Data Synthesis & Strategic Reporting:

• Engineered automated data pipelines using Alteryx to ingest and synthesise disparate datasets (transactional, operational, and third-party market data), creating a "single source of truth" for strategic analysis.
• Built dynamic Power BI executive dashboards to visualise complex financial narratives, translating technical data into actionable insights for Board-level stakeholders, which is aligning with the need to deliver strategic reporting on the AI landscape.

Investment Valuation & Financial Analysis:

• Led independent valuation assessments for Private Equity portfolio companies (across Asia and UK) under IPEV guidelines. Critically assessed financial models, challenging assumptions on market comparables (multiples) and discounted cash flows (DCF), which skills are essential for evaluating AI lab valuations and acquisition targets.
• Analysed tech-enabled business models and software KPIs (ARR, Churn, Net Retention) to verify fair value, demonstrating the ability to translate technical metrics into financial performance indicators.

Infrastructure & Asset Diligence:

• Supported complex M&A transitions for Real Estate clients, reviewing valuation models for large-scale physical assets. This experience provides a solid foundation for understanding the capital-intensive economics of AI infrastructure (Data Centers) and the "supply side" of compute.

Risk Modelling & Stress Testing:

• Conducted liquidity and capital adequacy analyses ("going concern") to evaluate the financial resilience of investment funds. This mirrors the need to assess the sustainability of competitor burn rates and the long-term viability of AI startups in the current market.

Cross-Functional Project Leadership:

• Managed multi-geography engagement teams, coordinating with Tax, Valuation, and Offshore Delivery Centers (India, Poland). Successfully acted as the central "intelligence node" for client data, ensuring disparate teams delivered cohesive financial insights to global stakeholders.