Middle / Senior Data Analyst

As a Middle/Senior Data Analyst at Playa AI, your primary responsibilities include analyzing complex datasets to derive invaluable insights, formulating hypotheses for product improvements, and conducting thorough A/B test analyses. You’ll also be creating interactive dashboards using Tableau to visualize trends and present findings, making your role crucial in driving data-informed decision-making.

To be eligible for the Middle/Senior Data Analyst position at Playa AI, candidates should have a minimum of 3 years of experience as a data or product analyst. Proficiency in SQL and Python is essential for processing and analyzing data. A strong command of English (B1+) is also necessary, along with an understanding of statistics and practical experience with BI tools such as Tableau or Power BI.

The interview process for the Middle/Senior Data Analyst position at Playa AI consists of three main stages. It begins with a 45-minute recruiting interview, followed by a technical interview lasting 60 minutes. Finally, successful candidates will meet with the CPO and CEO for a 30-minute chat. This structured approach ensures a comprehensive understanding of candidate skills and alignment with company values.

As a Middle/Senior Data Analyst at Playa AI, you’ll utilize various tools to perform your job effectively. Key tools include SQL for database querying, Python for data processing and visualization, and Tableau for developing insightful dashboards. Familiarity with AWS and BI tools will also enhance your data analysis capabilities and contributions.

In your role as a Data Analyst at Playa AI, you can expect to work on exciting projects related to player behavior analysis. You’ll develop detailed segments to identify engagement patterns, analyze A/B tests to optimize game recommendations, and create dashboards that provide deep insights to support product decisions, ultimately enhancing player experiences.

Data Analysts working at Playa AI can enjoy a variety of benefits, including an annual education budget of $600 to help with professional development and access to professional English courses. Additionally, employees receive medical insurance, ensuring support for their health and well-being as they contribute to the dynamic iGaming space.

While experience in the iGaming industry is preferred for the Middle/Senior Data Analyst position at Playa AI, it is not strictly required. Candidates with solid data analysis skills and a passion for the gaming sector will find opportunities to learn and grow within the role, leveraging their skills to make impactful contributions.

When answering this question, emphasize your proficiency with tools such as SQL and Python, and detail specific projects where you used these tools to drive results. Mention your ability to create dashboards in Tableau, showcasing your analytical skills in visualizing and interpreting data.

Begin by highlighting the project's context, challenges you faced, and the analytical methods you employed to address them. Focus on your problem-solving skills and the successful outcomes, such as increased efficiency or improved decision-making, to demonstrate your impact as a Data Analyst.

Discuss your systematic approach to A/B testing, including how you define hypotheses, select metrics for success, and analyze results. Highlight any particular case studies you've worked on, explaining the impact of your findings on product decisions, ultimately showing your analytical rigor.

Describe your preferred visualization tools, particularly Tableau, and explain how you select the right visuals to communicate your data effectively. Discuss how your reporting techniques enhance stakeholders’ understanding of insights, helping inform key business decisions.

It’s vital to convey your understanding of data validation, cleaning processes, and ongoing monitoring practices that help maintain data quality. Share examples of how you’ve conducted audits or checks in previous roles to reassure interviewers of your commitment to accuracy.

Be specific about the scripting languages you’ve used, particularly Python, and how you’ve automated data transformation processes. Offer examples of past projects that illustrate your ability to streamline workflows through effective scripting, enhancing operational efficiency.

Share a specific instance where data insights you uncovered led to a concrete business action, such as product enhancements or marketing strategies. Explain the journey from data collection through analysis to the ultimate business impact to demonstrate your value as a Data Analyst.

Discuss your strategies for simplifying complex data findings, such as using clear visuals or analogies that resonate with your audience. Highlight your past experiences where you successfully communicated insights to non-technical stakeholders, fostering understanding and informed decision-making.

Explain any exposure you have to machine learning, especially in the context of player behavior analysis or similar applications. Discuss specific projects where you utilized ML models, detailing the outcomes and learnings from the process to show your ability to leverage advanced analytics.

Describe your methods for task prioritization, such as setting deadlines based on project impacts or using tools for task management. Provide examples of past experiences where your organizational skills allowed you to efficiently manage competing priorities while delivering on time.