Data Analyst

We are looking for a Data Analyst with strong expertise in mobile game monetization who can bring an external perspective and deep domain knowledge to the team.

You will work at the intersection of analytics and data science: conducting monetization research, building predictive models, and directly influencing UA strategy, monetization decisions, and product development across the portfolio.

What are you working on?

• Genres: Puzzle
• Platforms: Mobile, iOS, Android

For which tasks (responsibilities)?

1. Conduct structured product and market research.

2. Analyze hybrid monetization models — IAA + IAP — including the balance between advertising revenue and in-app purchases, and propose actionable improvements.

3. Research market benchmarks, competitor strategies, and new monetization formats.

Predictive Modeling & Optimization

1. Build models for eCPM prediction, pLTV including ad revenue, and the impact of ad frequency on retention and revenue.

2. Research and apply relevant industry approaches, including ad placement optimization, IAP pricing, rewarded vs. interstitial trade-offs, and bid landscape analysis.

3. Formulate and validate hypotheses based on research, from academic papers to industry case studies.

Tech stack

Snowflake · dbt · Python · SQL · Firebase · AppLovin MAX · Adjust

What kind of professional are we looking for?

1. 2+ years of experience in mobile game analytics, preferably in F2P, casual, or mid-core games

2. Strong hands-on experience with IAA: eCPM, mediation, waterfall / bidding, ad networks

3. Experience with hybrid monetization: IAA + IAP

4. Strong SQL and Python skills

5. Experience building ML models in production

Nice to have:

1. Experience with AppLovin MAX, ironSource, or other mediation platforms

2. Understanding of Adjust / attribution, SKAdNetwork, and Privacy Sandbox

3. Experience with dbt

What is important for us in a person?

Ability to formulate hypotheses and communicate insights clearly to non-technical stakeholders

Why do we enjoy working here?

Direct impact on products with 10M+ installs

Work with a modern data stack: Snowflake, dbt, GCP

A low-bureaucracy team where ideas quickly move from hypothesis to experiment to result