Data Analyst Intern

Amber is looking for an intern who treats AI as a working tool rather than a shortcut, someone who can move quickly with chatbots and coding assistants, yet still opens the source data to confirm that the answer holds up. If that sounds like how you already work, this internship offers live business problems, real stakeholders, and a team that is actively shaping its AI-first analytics practice.

Why This Role Matters

Amber helps students book long-term accommodation near their universities, and the company has grown to 1M+ units across multiple countries, backed by $21M in institutional funding led by Gaja Capital. At that scale, decisions about pricing, supply, conversions, and operations lean heavily on data. As an intern you will be producing analyses that teams actually use, not mock assignments created for training purposes.

The hiring team is clearly looking for judgment, not just tool familiarity: AI output that has been verified, and recommendations that a non-technical stakeholder can act on.

Work Environment And Schedule

The afternoon-to-evening shift suggests overlap with international teams and stakeholders, so reliable availability and clear communication will count for a lot.

A Typical Day In This Role

Expect your time to be split between analysis, dashboard upkeep, and stakeholder communication. A realistic day might begin with reviewing a metric that moved unexpectedly, writing a SQL query to isolate the cause, and using an AI assistant to draft or debug the logic. You then verify the output against the raw tables, update the relevant dashboard, and summarize what you found for the team that requested it.

Alongside project work, you will document the prompts, workflows, and automations you create, so the wider analytics team can reuse them. This habit of documentation is something many interns overlook, and it is clearly valued here.

Core Responsibilities Explained

Technical Skills To Bring

The must-have list centers on SQL, specifically joins, aggregations, and window functions. Alongside this you should be comfortable with Excel or Google Sheets (pivots and lookups) and have working knowledge of Tableau and/or Power BI. Python with pandas is listed as a bonus, as is familiarity with APIs, MCP, or connecting AI tools to data sources. Experience with Metabase, GA4, or product analytics tools will also help your profile stand out.

SQL Excel Tableau Power BI Python pandas GA4 Metabase

The AI Skills Amber Expects

This is where the role differs from a standard analyst internship. The company expects regular, hands-on use of AI chatbots for real work, plus basic experience with at least one AI coding tool such as Claude Code, Cursor, Codex, or Copilot.

A project you built with AI, even a rough or half-broken one, carries more weight than a long list of tools you have only tried casually.

Equally important is the habit of checking AI output against the source data. Be ready to explain how you caught an error, because that story is part of the application itself.

What To Prepare Before Applying

Applications without a project link will not be considered

Your application needs more than a resume. Prepare the following:

1. A link to something you built with AI, such as a GitHub repo, live demo, Loom walkthrough, or Notion write-up

2. A short note of 3 to 5 lines covering what it does, which AI tools you used, and one thing the AI got wrong that you had to fix

Choose a project where you can honestly describe a mistake the AI made. A specific, candid example of a wrong join, a misread column, or a hallucinated metric shows exactly the verification habit the team is hiring for.

Eligibility Snapshot

How The Selection May Flow

The posting does not describe the interview stages, so the diagram below shows a likely path based on the application requirements rather than a confirmed process.

flowchart LR
A[Resume + Project Link] --> B[Project Review]
B --> C[SQL / Analytics Round]
C --> D[Final Discussion]

Skills That Will Grow Faster Here

Working with live data across business, operations, and product teams builds range quickly. You will sharpen SQL beyond textbook exercises, learn how dashboards are maintained when requirements keep shifting, and practice explaining numbers to people who do not care about the query behind them. You also get to see how an analytics team designs AI-first workflows, which is a differentiator in the current job market.

Strong analytical thinking, consistency, approachability, and communication are the soft skills the role stresses, so expect these to be tested as much as your technical ability.

Things Worth Learning Before Applying

Revisit window functions such as ROW_NUMBER, RANK, and LAG, since they appear often in real reporting work. Practice building a small dashboard from a public dataset in either Tableau or Power BI. If you have time, try connecting an AI tool to a data source and note where it goes wrong, as that experience feeds directly into your project write-up.

Keywords for Resume

AI Data Analyst • SQL • Window Functions • Tableau • Power BI • Excel • Google Sheets • Python • pandas • Data Visualization • Dashboarding • Claude Code • Cursor • ChatGPT • Prompt Engineering • Data Validation • Business Analytics • Product Analytics • GA4 • Metabase • Stakeholder Reporting

Final Thoughts

This internship suits freshers who already experiment with AI and care about getting numbers right. Amber offers live projects, a fast-moving startup setting, and the chance to help shape how an analytics team works with AI. If you have built something, even imperfectly, and can explain what you fixed along the way, you are exactly the kind of candidate this role is designed for.