Analyst

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

We are looking for an intern to join our Fuel Oil Trading Desk in Singapore.

The desk trades paper fuel oil across the East-of-Suez market, with Singapore as the key pricing and trading hub. One of our key advantages is understanding the physical market before it is fully reflected in prices — where cargoes are loading, where they are heading, and what this means for supply and demand in the weeks ahead.

As an intern, you will work directly with the trader and analyst to maintain and develop our fuel oil ship-tracking framework, and turn physical market observations into signals the trading desk can act on.

What you will do

• Track fuel oil and residue cargoes into and out of Singapore, the Straits, Middle East, Northwest Europe and the Mediterranean using Kpler, broker reports and port data
• Maintain a weekly database of fixtures, loadings, discharges and floating storage, including vessel classes and estimated cargo volumes
• Identify and investigate anomalies such as unusual routings, ship-to-ship transfers, extended waiting times and floating storage builds
• Convert tracking data into a rolling supply/demand balance and cross-reference it with the paper market
• Prepare concise, decision-oriented market updates for the trading desk
• Build and maintain Python tools using pandas and APIs to automate data collection, cleaning and visualisation
• Explore simple backtests to test whether physical tracking signals have predictive value for market prices

What you will learn

• How physical fuel oil moves through the global supply chain — from refinery residue and blending to shipping, storage and bunkering
• How to interpret ship movements, draught changes, floating storage and routing patterns as market signals
• How physical fundamentals translate into fuel oil pricing and paper-market structures, including Singapore 380 cst, 0.5% swaps, Hi-5, East-West spreads and timespreads
• How traders build, test, size, hedge and exit market views
• How to turn large amounts of raw data into a clear, actionable trading thesis
• Practical quantitative skills including API integration, pandas, time-series analysis, data reconciliation, visualisation and basic backtesting
• How a real commodity trading desk operates and responds when a market thesis breaks

What we are looking for

We welcome students from all academic backgrounds and years of study who have a genuine interest in commodity markets.

Required:

• 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
• Advantageous but not required:
• Exposure to oil, commodities, shipping or financial markets
• Experience with APIs, time-series data or quantitative analysis
• Familiarity with Kpler or other shipping/commodity data platforms

You do not need to be an oil-market expert. What matters most is curiosity, analytical ability and the willingness to learn how physical markets connect to prices. AI tools can be used to support your Python development, but you should be comfortable understanding and working with the code.

Period: December 2026 – June 2027, approximately 6 months

Commitment: Full-time during vacation periods preferred; part-time during term time is available, with a minimum commitment of 4 days per week

Eligibility: Students from all academic backgrounds and years of study