Data Analyst Intern (Finance) - January to May 2027

Coinhako; Singapore; On-site; SGD 20,000 - 27,000; Part time

Benefits offered by this job

CBD office location

Well-stocked pantry

Job summary

Coinhako is seeking a Data Analyst Intern in Singapore to join the data team and work on the numbers Finance relies on. You will write SQL and Python, reconcile figures, and automate checks that currently run manually.

Your work will involve building dashboards and documenting what a dataset means and excludes, with an emphasis on careful analysis and clear communication.

Qualifications

• Currently studying in a numerate field and eager to apply analytical skills.
• Strong SQL and Python skills for data analysis and automation.
• Attention to detail and ability to spot when numbers don’t add up.
• Clear written communication to explain discrepancies to non-technical stakeholders.

Responsibilities

• Check that numbers are correct and reconcile figures with independent sources.
• Automate manual checks and build reliable data pipelines for finance.
• Write SQL and Python to pull, compare and validate financial data.
• Explain discrepancies clearly and document data lineage.

Skills

SQL

Python

Attention to detail

Clear communication

Education

Currently studying in a numerate field (data, statistics, finance, CS, engineering)

Tools

Power BI

Tableau

QuickSight

Job description

We're looking for a Data Analyst Intern to work with our data team on the numbers Finance relies on. Every financial report, reconciliation and month-end figure at Coinhako depends on data being right. You'll work on the analysis and checks behind those numbers — reconciling figures against independent sources, investigating why two reports disagree, and turning checks that someone currently does by hand into something that runs on its own. This is real work on production data, scoped so you can finish things. You'll be given problems with a clear question and a clear finish line, and you'll have someone to ask when you get stuck. A number being \"right\" is not always obvious. No single source is definitive — venues disagree, references lag, and a figure that looks wrong is often just the market moving. You'll learn how we decide what to trust, and why \"I'm not sure yet, here's what I checked\" is a better answer than a confident wrong one.

Day to day

• Do these two reports agree, and if not, why?
• Which figure is the right one to use?
• Can this check be automated so nobody has to remember to run it?

What You’ll Do

• Check that our numbers are correct
• Reconcile financial figures against independent sources and explain any differences you find
• Investigate when a report looks wrong, and work out whether it actually is
• Trace a number back to where it came from
• Automate the manual checks — take a check someone currently runs by hand each week and turn it into something scheduled and reliable
• Write SQL and Python to pull, compare and validate financial data
• Make missing data visible rather than silent
• Make the reporting easier to use
• Build and maintain dashboards Finance uses to monitor financial performance
• Document what a dataset means and what it excludes, so the next person doesn't have to ask

What We’re Looking For

• No professional experience needed. We care about how you think and how carefully you work.
• Currently studying, or recently graduated, in a numerate field — data, statistics, finance, accounting, computer science, engineering or similar.
• SQL — you've written queries with joins and aggregations, and you can read someone else's.
• Python, for analysis or automation.
• You are careful with numbers.
• You check your own output before you show it to anyone, and you notice when a total doesn't add up.
• You are comfortable saying \"I don't know.\" (We would much rather hear that than a confident answer that turns out to be wrong.)
• You ask why a number is what it is, not just what it is.
• Clear written communication — a lot of this job is explaining a discrepancy to someone who isn't technical.

What You’ll Learn

• How financial reporting and reconciliation actually work in a live crypto business
• How to decide which number is the right number when several sources disagree
• Building and running automated data checks and pipelines
• Working with production data properly — version control, review, and not breaking things
• Using AI tooling well: we provide it, and we'll show you how we use it here

Nice To Have

• Coursework or personal projects involving financial, accounting or transaction data
• Any experience with dashboards — Power BI, QuickSight, Tableau, or similar
• Exposure to spreadsheets at scale, and an understanding of where they stop being safe
• Interest in crypto or trading

What’s in it for you

• Friendly and fun start-up work culture
• Convenient work location located in the heart of CBD area
• Vibrant office with a well-stocked pantry