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Coffee Analyst

Job in City Of London, Central London, Greater London, England, UK
Listing for: Selby Jennings
Full Time position
Listed on 2026-06-01
Job specializations:
  • Finance & Banking
    Data Scientist
  • IT/Tech
    Data Scientist, Data Analyst
Salary/Wage Range or Industry Benchmark: 60000 - 80000 GBP Yearly GBP 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Location: City Of London

Systematic Coffee Analyst

Location:

London or Switzerland (flexible). Compensation:
Competitive base + performance-linked bonus.

We are partnering with a leading commodities trading house seeking a Systematic Coffee Analyst to join a growing quantitative and research-driven trading function. This role sits at the intersection of data science, market intelligence, and systematic trading, focused specifically on the global coffee markets.

The position offers direct exposure to senior traders and the opportunity to materially impact strategy development, signal generation, and trading performance across both futures and physical-linked markets.

Key Responsibilities
  • Develop and maintain systematic models to analyse coffee market dynamics across Arabica and Robusta
  • Build data pipelines incorporating fundamental, macro, weather, and positioning datasets
  • Generate actionable trading signals to support discretionary and systematic strategies
  • Work closely with traders to translate quantitative insights into PnL-generating ideas
  • Conduct deep-dive research into supply-demand balances, crop cycles, and regional flows
  • Monitor market structure, spreads, volatility and liquidity across ICE and related instruments
  • Continuously improve modelling frameworks, backtesting processes, and execution assumptions
Requirements
  • Strong academic background in a quantitative field such as Mathematics, Physics, Engineering, Economics or Data Science
  • Experience in commodities research, systematic trading, or quantitative modelling
  • Exposure to agricultural markets, ideally coffee, though other ags experience is relevant
  • Proficiency in Python or similar programming languages for data analysis and modelling
  • Familiarity with time series analysis, statistical modelling, and signal generation
  • Strong commercial mindset with an interest in translating data into trading outcomes
  • Ability to work in a fast-paced, front-office environment alongside traders
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