Analyst - Publisher Monetization

This analyst works on the revenue side of ad-tech for app and game publishers. The core of the job is reading how a publisher's ads perform: revenue, eCPM, fill rate, impressions and bid rates, followed over time to see which way each is moving. Where something lags, whether a placement, a country, an ad format or a demand source, you propose what to do next.

Floor price optimization is the headline task. You look at how bids are distributed, how buyers behave and how good the inventory is, adjust the floors, and then check what the adjustment achieved. You also run experiments and A/B tests on monetization setups and write up results so the conclusion is obvious. Dashboards and recurring reports, for internal teams and for publishers, are yours to build and keep current.

Account managers are your closest colleagues. You prepare performance reviews, answer questions that need data, and raise risks or openings you notice in a publisher's account. When a client conversation is needed, you walk them through results and agree optimisation plans. Product, engineering and demand teams are the others you coordinate with when data or performance goes wrong.

The role is meant for fresh graduates of the 2025 and 2026 batches from top-tier institutions. A Bachelor's or Master's degree is expected, preferably in a quantitative field such as Computer Science, Statistics, Mathematics, Economics or Engineering.

• Sound analytical and mathematical ability, with a knack for turning data into conclusions someone can act on.
• Comfort with statistics: regression, correlation, hypothesis testing and distributions.
• Good command of Excel or Google Sheets. Some working knowledge of SQL is strongly preferred.
• Clear writing and speaking, so findings can be explained simply.
• An orderly approach to problems, attention to detail, and curiosity about why the numbers look the way they do.
• Willingness to support account managers and talk to clients when required.

Extras that count in your favour: Python or R, a BI tool such as Tableau, Looker or Power BI, basic knowledge of digital advertising (programmatic, RTB, header bidding, mediation), and any internship, project or competition that involved data analysis.

• Refresh your statistics, especially hypothesis testing and regression, and practise explaining each in everyday words, since the job involves presenting findings to non-analysts.
• Practise SQL with grouping, filtering and joins. A small project built on queries gives you something concrete to show.
• Make a compact dashboard in Tableau, Power BI or Looker Studio from any public dataset, and be ready to say which decision it helps with.
• Learn the vocabulary of ad monetization, such as eCPM, fill rate, header bidding and floor prices, so the terms feel familiar in an interview.
• If you have a data project or competition entry, describe it as a question, a method and a result.