Freight & Asset Research Analyst – London

Freight & Asset Research Analyst – Shipping & Freight Markets | London

A London-based shipping group that owns, charters, and trades tonnage across tanker and dry bulk markets is building a data team. The brief is specific – identify mispriced ships, time exposure to volatile freight markets, and quantify the risk behind every commercial position. They’re hiring a quantitative analyst to work alongside the Head of Data as a sparring partner and a second set of quantitative eyes.

The infrastructure to ingest, clean, and model data is already in place. What they need now is someone with the statistical instinct to interrogate it, separate signal from noise, and turn it into trade ideas the commercial desks can act on.

The work
Mispricing detection is the starting point. The team runs a live view of S&P and TC-in/out opportunities and needs someone to pressure-test the breakeven, valuation, and forward-curve assumptions behind each deal, then build a quantitative case for doing it or walking away. Right now they evaluate a handful of opportunities per week. The goal is hundreds.

Market timing runs alongside that. You’ll build and refine models that anticipate peaks and troughs in key tanker and dry bulk routes, starting with TD20, TD25, and TD3. Predictions are framed as distributions, not point forecasts, and the output feeds directly into chartering, hedging, and S&P timing decisions.

Risk and exposure work involves quantifying how exposed the fleet is to specific market scenarios, evaluating the cost and benefit of TC-in/TC-out decisions and derivatives overlays, and developing the sell/keep and opportunity-cost frameworks behind those calls.

Performance attribution rounds it out: measuring how calls played out, separating good decisions from good outcomes, and feeding the lessons back into the models.

You’ll also maintain and extend the proprietary datasets that underpin all of the above. You’ll spend time in code, with the expectation that you’re using AI coding assistants like Claude Code to move quickly. The goal is analytical output, not engineering polish.

Who fits
The strongest backgrounds are in statistics, econometrics, quant finance, or systematic research. Equity or commodities research, systematic trading, and fund analytics all translate well. Direct shipping experience is a genuine differentiator – analytical roles at a broker, owner, fund, or consultancy are particularly valued, and market intuition counts for at least as much as technical skill.

Python and SQL are the day-to-day tools. You don’t need to be a senior engineer, but you do need to be genuinely fluent and comfortable reading, modifying, and shipping analytical code. Engineers without market intuition and non-technical analysts will both find this a stretch.

They move fast, iterate, and rebuild. If you enjoy turning a vague hypothesis into a working prototype and scrapping it when the data says so, you’ll fit the pace.

3–5 years in a markets-facing analytical role: shipping research, commodities or equity research, quant or systematic trading, fund analytics, or comparable.

For more information, contact Liam Daly