Digital Marketing Data Scientist

• Develop statistical and machine learning models to assess and optimize the effectiveness of marketing campaigns.

• Analyze and interpret data to identify potential improvements in marketing strategies.

• Apply uplift modeling methods to target specific customer groups to maximize ROI.

• Collaborate with marketing and sales departments to understand business goals and translate them into analytical tasks.

• Prepare and present reports on analysis results and recommendations for marketing strategy enhancements.

• Evaluate and continuously improve analytics and modeling methodologies in line with the latest trends in Data Science.

• Participate in the development and implementation of systems and tools to automate analytical processes.

Requirements

• Over 2 years of experience in Data Science, with a focus on uplift modeling and causal effect analysis.

• Deep knowledge and practical experience with Python and data analysis libraries (Pandas, NumPy, Scikit-learn), as well as specialized libraries for causal analysis, for example CausalML or others.

• Understanding of A/B testing principles, including planning, conducting, and analyzing test results.

• Knowledge of SQL and experience with databases, including ClickHouse, for effective data extraction and processing.

Nice to have

• Knowledge and experience with Apache Spark and Apache Airflow for processing large data volumes and workflow automation.

• Experience with cloud platforms, particularly Google Cloud Platform, for scaling and managing analytical solutions.

• Familiarity with CI/CD principles, experience with model versioning, and understanding of MLOps fundamentals.

• Bachelor's or higher degree in Applied Mathematics, Statistics, Computer Science, Economics or a related field.

• Strong communication skills and the ability to effectively interact with both technical specialists and business stakeholders.