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.
