Senior Data Analyst - Casual Game

As a Senior Data Analyst at Voodoo, your primary responsibilities include analyzing large data sets to understand player behavior, providing actionable insights that influence game design and the product roadmap, and collaborating with cross-functional teams to implement data-driven strategies. You will also lead A/B testing, build automated dashboards, and establish best practices for data reporting and collection.

To excel as a Senior Data Analyst at Voodoo, candidates should have at least three years of analytical work experience in the gaming or tech industry, proficiency in SQL, R, or Python, and a solid understanding of statistical analysis methods, including A/B testing. Strong problem-solving skills and an attention to detail are also crucial for success in this role.

Voodoo is committed to supporting the professional growth of our employees, including Senior Data Analysts. We offer best-in-class compensation, access to ongoing training resources, and opportunities to work on innovative projects that allow analysts to expand their skills and expertise within the gaming industry.

Yes, Voodoo offers flexibility for Senior Data Analysts to work remotely, provided they reside within a two-hour time difference of the Central European Time Zone (CET). This allows for a better work-life balance while contributing to impactful projects at Voodoo.

Senior Data Analysts at Voodoo utilize a range of tools and technologies including SQL for database management, as well as R or Python for data analysis. They also interact with analytics software for A/B testing and build automated dashboards using various visualization tools to communicate insights effectively.

In your response, highlight specific instances where you’ve handled large datasets, describing the tools you used, the types of analyses you performed, and how your insights influenced business decisions or improved player engagement in previous roles.

Talk about your systematic approach to A/B testing, from defining the hypotheses to setting up the experiments, analyzing the results, and implementing changes based on data insights. Provide examples of successful A/B tests you’ve led.

Discuss your methods for validating data, including checks for data quality, implementing consistent data collection processes, and using statistical techniques to ensure robust and reliable results.

Share how you simplify complex data through visualizations, dashboards, and clear, tiered reporting, emphasizing the importance of storytelling with data to make insights accessible to all team members.

Illustrate your collaborative approach, highlighting your communication skills, ability to listen to different perspectives, and how you incorporate feedback into your data-driven strategies to ensure alignment with project goals.

Detail your proficiency in SQL, mentioning specific queries or techniques you’ve used to extract, manipulate, and analyze data, and how these efforts supported business decisions in your previous positions.

Discuss how you leverage statistical analysis to inform your recommendations, making sure to include your understanding of industry-standard methods and how you apply them in practical scenarios.

Be candid about a specific experience where the data did not support the anticipated outcome, explaining how you adapted your approach, what you learned from the experience, and how it ultimately helped you grow professionally.

Explain your prioritization process, emphasizing the importance of understanding the business impact of each task and how you use project management techniques to stay organized and efficient.

Share your commitment to continuous learning through attending workshops, online courses, networking with other professionals, and reading industry publications to ensure you’re incorporating the most current techniques and trends into your work.