Hybrid in Warsaw prefelably  but remote option is possible

• Provide data-driven insights and deliver production-grade solutions to maximize the value of our data.
• Research the latest machine learning technologies and keep up-to-date with industry trends and developments.
• Verify that the collected data is accurate, consistent, and free from errors.
• Design and implement next-generation machine learning models with advanced technologies.
• Create quick prototypes and proof-of-concepts for new features and products.
• Regularly test your audience targeting strategies and adjust them based on performance metrics.
• Closely work with ML Engineers and ML Ops Teams to deploy and streamline machine learning products and end to end pipelines on the advertising platform to drive business growth. Our models will use the data to make predictions and recommendations, such as selecting the most appropriate ad format, choosing the optimal target audience, and setting the right bid amount for each impression.
• Communicate with various stakeholders to understand business requirements, manage expectations and create effective roadmaps.
• Depending of your skills and experience you will have a chance to technically lead people.

• Degree in science or engineering fields.
• At least 5 years of proven industry experience.
• Problem-solving skills and creative thinking to address open challenges in various fields.
• Theoretical background and experience in data analytics, data mining, machine learning and statistics.
• Experience with ML libraries (e.g.: Scikit-Learn, TensorFlow, PyTorch, Spark ML, etc.) mainstream big data tools (e.g.: Spark, Snowflake, etc.).
• Programming skills in Python or OOP.
• Knowledge of SQL and databases.
• Experience in source code versioning tools (e.g.: git, etc.).

• PhD in science or engineering fields.
• Deep theoretical background in machine learning and/or data mining,
• Hands-on experience with production-grade machine learning solutions and/or software development.
• Experience with the advertising industry, recommendation systems or real-time bidding (RTB) ecosystem.
• Proficiency in mainstream mainstream big data tools and ML libraries.
• Proficiency in mainstream big data tools (e.g., Spark, Snowflake, etc.) and ML libraries (e.g., TensorFlow, PyTorch, Spark ML, etc.).
• Experience with CI/CD (e.g.: Github Actions, etc.), monitoring (e.g: Grafana, etc.), cloud solutions (e.g.: AWS, Sagemaker, etc.), A/B testing.