Our Customer: Our customer is a global, data-driven digital advertising technology company operating at large scale across mobile apps and web platforms. Your Tasks: * Analyze large, complex datasets to uncover patterns, insights, and business opportunities; * Design, build, and own scalable, end-to-end data pipelines; * Develop and productionize advanced machine learning models and algorithms, particularly in monetization-related domains; * Build and maintain data models for real-time (online) processing; * Contribute to the creation of new data-driven products and continuously improve existing ones; * Collaborate with Product, BI, Analytics, DevOps, R&D, and Marketing teams to deliver complete solutions; * Lead full production releases, including requirements analysis, testing, monitoring, result evaluation, and rapid response to critical issues.
Required Experience and Skills: * 6+ years of experience as a Data Scientist with a strong foundation in machine learning concepts and models; * Previous experience in the Ad-Tech industry; * Hands-on experience working on large-scale, high-load systems processing billions of requests per second; * Hands-on experience with Python including writing production-ready code and working with modern Python frameworks and tooling; * Experience with data science / ML libraries and models, such as regression and classification models (e.g. XGBoost, LightGBM), recommendation systems, and related ML techniques; * Solid understanding of databases and SQL for data analysis and retrieval; * Experience with monitoring and alerting tools such as Grafana and Kibana; * Proven experience working in real-time / online environments; * Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field; * Strong end-to-end ownership mindset: ability to take solutions from research and experimentation through implementation and production; * Fluent English with strong communication and collaboration skills.
Would Be a Plus: * Familiarity with the programmatic advertising ecosystem (DSPs, SSPs, ad exchanges); * Experience with relational databases (e.g. Vertica, VoltDB) and non-relational databases (e.g. MongoDB); * Experience working with PMML.
