Trading Operations Intern

HashKey Group; Singapore; On-site; SGD 16,000 - 27,000; Part time

Benefits offered by this job

Internship at trading firm

Job summary

HashKey Group is seeking a hands-on junior operations analyst to support the day-to-day live quantitative trading desk in Singapore. You will own defined daily checks from week one, scale them by month three, and automate at least one recurring task.

You will learn how a quantitative desk runs inventory, funding, fees, and venue relationships, while building operational tooling with an AI-native team. This internship focuses on practical exposure rather than shadowing.

Qualifications

• Ideal candidate is penultimate/final-year undergraduate, master's student or recent graduate in related fields.
• Strong numeracy and attention to detail essential; you spot when numbers don’t tie out.
• Exposure to AI-enabled tools, automation, and data dashboards is a plus.
• Ability to explain market maker roles and crypto market structure.

Responsibilities

• Daily desk operations: run morning balance and inventory checks across exchanges and chains; flag breaks and lift early.
• Reconciliation: compare exchange and on-chain balances against internal ledger; investigate and document differences.
• Venue and account admin: maintain exchange account records, API key inventory, fee-tier status and onboarding checklists.
• Reporting: prepare inputs for daily and weekly desk reports to management.
• Automation: convert at least one recurring manual check into a script or dashboard using Python/SQL and internal tools.
• Ad hoc: support traders and engineers on operational questions as they arise.

Skills

Numeracy

Attention to detail

Crypto market knowledge

Explain market maker

SQL/Python

Data dashboards

AI-enabled tools

Workflow automation

Education

Undergrad/Grad student

Tools

Python

SQL

On-chain data platforms

APIs / Data dashboards

Job description

You will support the day-to-day operations of a live quantitative trading desk. This is not a shadowing internship. From week one you will own a defined set of daily checks, and by month three you should be running them independently and have automated at least one of them.

What you will do

Daily desk operations: run morning balance and inventory checks across exchanges and chains; flag breaks and lift early

Reconciliation: compare exchange and on-chain balances against our internal ledger; investigate and document differences

Venue and account admin: help maintain our exchange account records, API key inventory, fee-tier status and counterparty onboarding checklists

Reporting: prepare inputs for daily and weekly desk reports to management

Automation: turn at least one recurring manual check into a script or dashboard using Python/SQL and our internal data tools

Ad hoc: support traders and engineers on operational questions as they come up

What you will learn

How a quantitative trading desk actually runs: inventory, funding, fees, venue relationships

Operational controls at a firm where an unexplained break is treated as a real problem, not a rounding error

How to build operational tooling with an AI-native team

Who we are looking for

Able to commit at least 3 days per week for a minimum of 6 months, with a consistent weekly schedule.

Penultimate or final-year undergraduate, master's student, or recent graduate in finance, economics, engineering, computer science, mathematics or a related field

Strong numeracy and attention to detail: you notice when a number doesn't tie out

Genuine interest in crypto market structure and quantitative trading; you should be able to explain what a market maker does

Exposure to AI-enabled tools, workflow automation, data dashboards, SQL/Python, or on-chain data platforms is an asset

Exposure to traditional financial market structure, market participants and the evolving regulatory landscape across major jurisdictions is a plus

Nice to have

• Internship at a trading firm, exchange, fintech or fund
• Personal trading or on-chain experience; side projects with real data