Fuel Oil Market Data Intern - Trading Signals & Python

Conda Capital Pte. Ltd.; Singapore; On-site; SGD 13,000 - 20,000; Full time

Job summary

Conda Capital Pte. Ltd. in Singapore is seeking an intern for its Fuel Oil Trading Desk.

You will work directly with the trader and analyst to develop ship-tracking capabilities and translate market observations into actionable signals for the desk. You will learn about how physical fuel oil moves through the global supply chain, interpret ship movements and routing patterns as market signals, and build quantitative tools using Python, pandas, APIs and basic backtesting to support trading

Qualifications

• Working knowledge of Python, particularly pandas and basic data visualisation.
• Strong analytical and problem-solving skills.
• Curiosity and willingness to learn.
• Ability to work with large amounts of data and identify patterns or anomalies.
• Good written and verbal communication skills.

Responsibilities

• Track fuel oil and residue cargoes into and out of Singapore and surrounding regions.
• Maintain a weekly database of fixtures, loadings and volumes.
• Identify anomalies such as unusual routings or floating storage builds.
• Convert tracking data into a rolling supply/demand balance and compare with paper market.
• Prepare concise, decision-oriented market updates for the trading desk.
• Build and maintain Python tools using pandas and APIs to automate data tasks.
• Explore simple backtests to test predictive value of signals.

Skills

Python

Pandas

Data visualization

Analytical skills

Communication skills

Tools

Kpler

APIs

Job description

Conda Capital Pte. Ltd. in Singapore is seeking an intern for its Fuel Oil Trading Desk.

You will work directly with the trader and analyst to develop ship-tracking capabilities and translate market observations into actionable signals for the desk. You will learn about how physical fuel oil moves through the global supply chain, interpret ship movements and routing patterns as market signals, and build quantitative tools using Python, pandas, APIs and basic backtesting to support trading