Senior Data Scientist (f/m/d)

Job description

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 Tensorflow and 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. Your Mission & Who We Are Looking For: Proven track record in production ML. You have 5+ years in Data Science with a history of deployed models that moved real business metrics, not just research that stayed in notebooks. At adjoe, you'll be building models that predict LTV, conversion, and user behavior across 770 million users, directly impacting advertiser ROAS and publisher revenue. Deep learning is your primary tool. You have strong hands-on experience with PyTorch or TensorFlow and have deployed deep learning models in production environments handling 1M+ daily predictions. You know the difference between a model that works in evaluation and one that holds up under real traffic. Full ML lifecycle ownership. You own the problem end-to-end from extracting insights out of terabytes of behavior…