Financial Quant

About the role

UrbanChain is building a team of passionate individuals dedicated to delivering positive impact through innovative technological and commercial solutions. We’re hiring across two quant streams:

• 2x Commercial Finance Quant — reporting to the Head of Commercial Finance
• 1x Structured Finance & Treasury Quant — reporting to the Head of Structured Finance

Working closely with Financial Control, Client Operations & Portfolio Optimization, the Financial Quants will play a critical role in driving business performance through quantitative financial analysis, modelling, and decision support.

Commercial Finance coverage

• Contribution margin by channel/segment/deal and gross profit per channel FTE
• Cost of acquisition (fully loaded CAC / GP) and payback period by channel
• Cost to serve per customer / MPAN / MWh
• Win rate by channel/segment and pipeline conversion velocity
• Forecast accuracy (90–180 day, revenue and GP)
• Margin drift vs. pricing guardrails
• Win probability model by channel, segment, deal size, and cycle stage
• Margin risk / erosion model (volatility, shape risk, volume variance vs. signed margin)
• Pipeline-to-cash conversion forecast (timing + confidence bands)
• Channel scalability & saturation curve (diminishing returns vs. volume / FTE)

Structured Finance & Treasury coverage

Liquidity & Cashflow

• Short-term and medium-term liquidity coverage ratio (rolling 30 / 90 / 180-day horizons)
• Cashflow-at-Risk (CFaR) by channel / product / segment
• Daily minimum cash balance breach probability
• Stress-adjusted liquidity runway under adverse scenarios
• Cashflow forecast accuracy by horizon (7 / 30 / 90 / 180 days)
• Treasury forecast backtesting and model stability metrics

Capital & Funding

• Weighted average cost of capital (WACC) by funding source
• Marginal cost of liquidity by tenor and instrument
• Funding concentration risk by lender, tenor, and instrument
• Refinance risk curve (time-to-maturity vs exposure)
• Optimal funding mix optimisation (cost vs resilience trade-off)
• Interest Rate Sensitivity (DV01 / PV01) at portfolio and entity level
• Earnings-at-Risk (EaR) from interest rate movements

Deliverables

• Automated cashflow and liquidity forecasts
• Scenario analysis to support funding and investment decisions
• Pricing and commercial finance analysis
• Cross-functional collaboration with finance, risk, and settlements teams
• Compliance & risk infrastructure: delegation of authority, finance controls, risk capture and communication
• Treasury and liquidity reporting
• Balance-sheet and P&L analytics
• Risk and exposure monitoring

Requirements

• Master’s degree in financial mathematics, statistical analysis, data science, financial engineering, or computational finance
• CFA or ACCA preferred
• Quantitative finance experience paramount with a background in financial data modelling
• 2–5 years experience in energy or fintech markets and knowledge of business key drivers
• Preferred understanding of renewable energy markets and/or structured capital markets
• Strong analytical and comprehension skills
• Experience working with analytical tools and programming languages to manage large datasets
• Excellent communication skills, with the ability to present complex data and insights clearly