Lead Data Scientist

Founding Data Scientist | GreedyGame

At GreedyGame, we are building at the intersection of app monetization, user acquisition, adtech, and growth.

Through PubScale, we help apps and game developers scale monetization and growth through products across AdX, Offerwall, user acquisition, and related growth solutions. We are a company built on experimentation, questioning the status quo, and solving real business problems and that is exactly the mindset this role needs.

This role is different.

We already have people in the broader data setup, but this is not a conventional data science role.

This is not for someone looking to inherit a perfectly structured function, plug into a mature playbook, or wait for clean problem statements to arrive.

This is for someone who gets excited by ambiguity, sees messy systems as opportunity, and wants to build a high-impact data science charter from the ground up.

We are looking for a Founding Data Scientist who wants to shape the roadmap, solve meaningful business problems one by one, and eventually build a team under that charter.

This will not be a comfortable job.

It will be a meaningful one.

In this role, you will help us answer questions like:

• What should we optimize first across monetization, UA, and publisher growth?
• Where are we losing revenue, efficiency, or decision speed?
• Which patterns matter, and which are just noise?
• What models, frameworks, or systems should exist here that do not exist today?

PubScale operates in a space where better data decisions directly impact installs, DAU quality, LTV, ROI, revenue uplift, and monetization performance. So this role needs someone who can connect data work to real commercial outcomes.

Candidates who have worked extensively with direct consumer data, real-time data systems, and B2C product environments will be a particularly strong fit.

What youll do

• Build the data science charter for a fast-moving adtech and app growth business
• Identify high-value opportunities across monetization, user acquisition, experimentation, pricing, segmentation, and optimization
• Create models, decision systems, and analytical frameworks that improve business outcomes
• Work closely with product, business, engineering, and leadership to translate ambiguous problems into clear execution paths
• Bring rigor to experimentation, measurement, and prioritization
• Help us move from reactive analysis to proactive decision-making
• Over time, build the team and standards for this function

Youll likely do well here if:

• You are deeply startup-minded and enjoy building in imperfect environments
• You have solved real business problems end to end, not just contributed small pieces
• You know how to bring structure to ambiguity
• You are comfortable operating without heavy mentoring or handholding
• You are seen as a subject matter expert in your space
• You can explain complex ideas with extreme clarity
• You care more about impact than optics

This role is probably not for you if:

• You are early in your career and still need a lot of direction
• You have 3 years or less of experience
• You are looking for a highly comfortable, low-ambiguity environment
• You prefer working only on narrowly defined tickets
• You have not yet driven visible business impact in your previous roles.

This is not an entry-level or early-career role. We are intentionally looking for someone with enough depth, maturity, and ownership to operate in ambiguity and create meaningful business impact from day one.

What were looking for

• Strong experience in Data Science, Applied Analytics, Decision Science, or a related domain
• Proven examples of solving business-critical problems with measurable impact
• Strong foundation in statistics, experimentation, modeling, and product/business thinking
• Experience in fast-paced startup or high-growth environments
• Ability to influence cross-functional teams and senior stakeholders
• High ownership, strong clarity, and excellent communication

Bonus if youve worked in:

Adtech, gaming, marketplaces, growth, monetization, or user acquisition

Skills

LLM workflows, Neo4j, A/B experimentation, Python, MLOps practices, time series forecasting, SQL

If you are someone who wants to build, not inherit and wants your work to directly shape business outcomes wed love to hear from you.