Working Student Data Science Intern

adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we've become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually.

Architecting Intelligence to Optimize 200M+ Daily Decisions

As the intelligence core of our engineering organization, our Data Science team doesn't just deploy models, we engineer the fundamental decision engine that powers our platform. At a scale of 770 million users and 100,000+ predictions per second, we are solving a multi-objective optimization problem that balances user incentives, advertiser ROI, and long-term platform health in real time.

Our architecture is built on a 1PB+ behavioral data lake, providing the high-fidelity input necessary to train deep learning models that predict individual user engagement with precision. We aren't just optimizing clicks, we are dynamically calculating optimal reward structures to sustain a global value exchange.

Engineered for performance, our stack leverages PyTorch for model training, NVIDIA Triton to achieve sub-100ms inference. We own the full ML lifecycle from high-level research and feature engineering to deployment and A/B experimentation. Here, you will find the autonomy, the data depth, and the massive scale required to solve the most complex optimization challenges in the adtech ecosystem.

The data infrastructure behind this runs at real scale: 2TB ingested in real time every day, 100+ Airflow jobs and data pipelines, and ML models handling p99 latency of 100ms across 100,000+ predictions per second.

Your Mission & Who We Are Looking For

• Quantitative Academic Foundation: You are currently pursuing a Bachelor’s or Master’s in Data Science, Computer Science, Mathematics, Statistics, or a related quantitative field. You are available to contribute up to 20 hours per week during the semester.

• ML Model Prototyping: You will support the research and evaluation of deep learning and machine learning models that predict user behavior across our 770 million user base. We are looking for solid Python skills and hands-on familiarity with PyTorch, TensorFlow, scikit-learn, and gradient boosting libraries (LightGBM/CatBoost/XGBoost) to prototype new algorithms.

• Large-Scale Data Exploration: Operating on our 1PB+ behavioral data lake, you will extract patterns from terabytes of data to engineer high-fidelity features for our training pipelines. This requires strong SQL fundamentals, an interest in distributed query engines (AWS Athena, Trino, Spark), and fluency with pandas, polars, and NumPy.

• Experimentation & Validation: You will collaborate closely with our data scientists to test your fit-for-purpose solutions against our multi-objective optimization problem. We need someone who can rigorously evaluate models through offline experiments and A/B tests before they hit our 100,000+ predictions-per-second production environment.

• Plus: ML Infrastructure Exposure: Any prior exposure to the systems that run our real-time scale—AWS, workflow orchestration (Airflow), containerization (Docker), or basic model deployment workflows—will accelerate your impact.

What’s in It for You?

At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day.

• Go Big. Own projects with impact on 770M users and push adtech boundaries.

• Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum.

• Be Direct. Solve problems openly and collaborate across teams.

• Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other.

• Have Fun. Celebrate wins, enjoy daily victories, and bring your energy.

Skip writing cover letters. Tell us about your most passionate personal project, your desired salary, and your earliest possible start date. We are looking forward to your application!

We welcome applications from people who will contribute to the diversity of our Company.

We welcome applications from people who will contribute to the diversity of our company.