Data Analyst, Product 

As a Data Analyst at PENN Entertainment, you will be responsible for leveraging complex data sets to answer pivotal questions regarding product feature performance. Your duties will also include creating custom reports, providing insightful analysis, and offering clear recommendations to business stakeholders to drive decision-making. You will support Intermediate and Senior Data Analysts in project initiatives and liaise with data engineers to optimize data pipelines.

To become a Data Analyst at PENN Entertainment, you should hold a university degree in a related field such as Computer Science, Statistics, or Business. Strong knowledge of relational databases and proficiency in SQL are critical, with the ability to write and troubleshoot complex queries. Familiarity with data exploration tools like Looker or Mode and excellent communication skills are also essential.

As a Data Analyst at PENN Entertainment, key skills include a passion for data analysis, an understanding of user interaction with digital platforms, and a strong quantitative approach to problem-solving. You should also embody excellent organizational abilities to multitask effectively in a fast-paced environment, along with the ability to clearly present complex data to stakeholders.

PENN Entertainment is committed to supporting the career growth of Data Analysts through structured mentoring programs, educational reimbursements, and opportunities for advancement within the organization. You’ll have the chance to learn from experienced professionals and help others in their development as well.

In a typical day as a Data Analyst at PENN Entertainment, you would engage with various product stakeholders, analyze complex data sets, and develop insights on product features. Your day might also involve creating and presenting reports, collaborating with data engineers on data pipeline solutions, and staying updated with industry trends to ensure your analytical work supports business objectives effectively.

In your response, highlight specific SQL projects you've worked on, describing how you wrote and optimized queries to extract meaningful insights from large data sets. Focus on your understanding of relational databases and your ability to troubleshoot complex scenarios.

Discuss your methodology for identifying data discrepancies, whether through methodical examination of source data or using tools. Mention your experience communicating issues with engineering teams and how you work collaboratively to resolve them.

Provide a detailed overview of a specific project, emphasizing the questions you sought to answer, the analysis you conducted, and the final decision that stemmed from your findings. Clarify how your insights directly impacted product strategy or performance.

Mention the data visualization tools you’ve worked with, such as Looker or Mode. Provide examples of how you’ve utilized these tools to create impactful visual reports that facilitated discussions with stakeholders.

Discuss your organizational skills and any tools you use for task management. Explain your approach to prioritizing analytical tasks based on impact, deadlines, and stakeholder needs, ensuring clarity in communication.

Share your strategies for continuous learning, such as following industry news, participating in webinars, or engaging in online courses. Emphasize your enthusiasm for leveraging new insights and technologies in your analytical work.

Explain your approach to data validation and verification, including the steps you take to ensure accuracy and reliability in your analyses. Mention any specific methodologies you utilize to confirm findings before communicating them to stakeholders.

Discuss key metrics and data points you focus on, such as engagement rates or feature usage. Describe your approach to user behavior analysis and how it informs recommendations for product enhancements.

Outline a scenario where you successfully communicated complex data insights to non-technical audiences. Highlight the techniques you used, such as storytelling or visualization, to ensure clarity and foster understanding.

Articulate your passion for the gaming, entertainment, and sports industries, and how PENN Entertainment's culture and commitment to innovation align with your career aspirations. Mention your excitement about contributing to a team focused on data-driven solutions.