Our Marketing Analytics team is looking for a Senior Data Analyst / Data Scientist!

For which tasks (responsibilities)?

• Participate in the development and improvement of our internal system of evaluating the effectiveness of continuous ad buying.

• Provide methodological support to the existing team, ensure the selection of appropriate tools for specific tasks, and guide the correct interpretation of results.

• Contribute to the automation of processes related to training, validation, monitoring, and updating of predictive models.

• Develop methods to account for and/or eliminate the effects of seasonality and product activity (A/B tests, LiveOps) to improve forecast accuracy and stability.

• Monitor forecast achievement, as well as look for and interpret the reasons of why forecasts are not met.

• Develop segmentation techniques to partition data (at the level of users, countries, etc.) into optimal groups.

• Implement and test new approaches to forecasting (e.g., neural networks, boosting algorithms, etc.).

• Work with the existing Python codebase, participate in code reviewing and optimization.

• Develop and test modular, reusable code in accordance with the best practices of mission-critical software development.

• Effectively communicate complex ideas and data-driven decisions to various stakeholders (CMO, user acquisition team, data engineering team, business analytics team).

• Write optimized queries and create templates for the PostgreSQL database.

• Write understandable documentation.

What kind of professional are we looking for?

• Bachelor's or Master's degree in statistics, applied mathematics, computer science, or a related field.

• At least 5 years of experience in data analytics, preferably in mobile advertising or marketing analytics.

• Proficiency in SQL and Pandas for data manipulation.

• Intermediate or higher-level Python programming skills.

• Experience in developing mission-critical software.

• Experience with version control systems (GitLab).

• Strong knowledge of statistical modeling, machine learning, and predictive analytics.

• Excellent problem-solving skills and attention to detail.

• Strong communication skills with the ability to communicate complex ideas.

Technical skills:

• Python (intermediate or advanced level).

• SQL (PostgreSQL).

• Git (GitLab).

• Machine learning libraries (e.g. scikit-learn, TensorFlow, PyTorch).

• Familiarity with Airflow is a plus.

Bonus skills:

• Experience with mobile apps (gaming experience will be a big plus) with ad and in-app monetization.

• Expertise in time series analysis and segmentation techniques.

• Experience with data visualization tools (Tableau).

• Intermediate written English for effective communication, including with LLMs.

• Familiarity with cohort analysis and key ad-buying effectiveness metrics (ROAS).

• Experience in creating Python packages.