About this role
The Principal Data Analyst on the Zynga Poker Analytics Team is responsible for leveraging data-driven insights to significantly impact the experience for millions of global players. The day-to-day work involves shaping product strategy by analyzing long and short-term trends to guide product direction. This role requires designing and executing statistically sound experiments to measure their impact on the game. Analysts will also maintain critical business intelligence dashboards and ETL pipelines to ensure the organization has accurate information regarding game performance. Furthermore, a key component of the job involves enhancing game integrity by improving fraud detection models and designing telemetry to capture meaningful player interaction data.
This position exists to bridge the gap between complex data analysis and actionable product and game design decisions. The analyst will partner closely with product teams to translate player behavior insights into tangible improvements in revenue, retention, and engagement metrics. They will also contribute to the Analytics Organization's AI initiative aimed at improving analytics workflows. This role is ideal for an analyst who enjoys solving complex analytical puzzles that have a large-scale impact and thrives in an environment where data directly influences the product roadmap.
Candidates who excel in translating complex data into simple, actionable terms and possess a strong sense of ownership over analytical challenges would be well-suited for this role. Success in this position requires a blend of technical data skills, strategic thinking, and strong collaborative communication abilities.
What you will do
- Collaborate with the Product team to enhance revenue, retention, and engagement metrics through A/B testing and insights analysis.
- Analyze player behavior to understand player motivations and preferences, translating findings into actionable experience improvements for game design.
- Design and maintain ETL pipelines to extract, transform, and load data from various sources, establishing the source of truth for analyses.
- Participate in and contribute to the Analytics Org’s AI initiative focused on improving analytics workflows.
- Design game telemetry to capture meaningful player interaction data to enhance the overall game experience.
- Design and maintain highly visible dashboards used by game leadership and designers for strategic decision-making.
- Support the economy team in tuning game features to optimize for long-term game and feature health.
- Play a leading role in the design and continuous improvement of fraud and bad actor models.
What you need
- A Bachelor's degree in Computer Science, Mathematics, Statistics, Economics, or a related quantitative field is required.
- A minimum of eight years in data science or analytics roles is necessary, with at least six years specifically in a Product Data Science or Gaming Analytics team preferred.
- Demonstrated experience guiding product teams through complex decisions and ambiguous data is essential.
- Proficiency in Python and SQL is a mandatory requirement for this role.
- Proven experience in data mining, data visualization, statistical analysis, and machine learning techniques is required.
- Familiarity with Business Intelligence (BI) tools such as Tableau and version control systems like Git is advantageous.
- Strong written and oral communication skills are necessary to explain complex data clearly.
- Experience or demonstrated interest in improving analytics team processes using LLMs is a plus.
Nice to have
- Familiarity with AI/ML concepts
- Experience in automating recurring analytics work
Benefits
- Location: Austin, TX; Toronto, Canada
Skills and tech stack
Questions candidates ask
What is the remote policy for this role?
The posting does not explicitly detail the remote work policy for this position.
What is the compensation structure?
The posting does not provide specific salary details for this role.
What is the primary tech stack used by the team?
The required technical skills include proficiency in Python and SQL. BI tools like Tableau and Git are also advantageous.
What is the team structure like?
The role involves collaboration with the Product team, game design, consumer insights teams, and other data analysts and scientists on the team.