WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers.

WHY GROWTH MEASUREMENT?

In this role, you will leverage your expertise in data science, statistics, and causal inference to develop measurement framework and product to deepen our quantitative understanding of growth efforts, which includes but not limited to performance marketing efficacy, attribution modeling and incrementality measurement. You will collaborate with cross-functional teams to develop and implement data-driven products and strategies that maximize the impact of our growth initiatives. You will also report to Senior Data Science leadership on the team.

You Will:

• Conduct comprehensive analyses and develop measurement framework for growth efforts using advanced statistical methods and causal inference methodologies
• Collaborate with marketing, product, and engineering teams to find opportunities for improvement and build data-driven solutions.
• Contribute to the development of a robust data infrastructure to support user growth.
• Communicate insights and discuss recommendations with cross function partners translating complex technical concepts into actionable insights.
• Partner with different product teams to optimize user growth strategies through insights, strategy, and leadership.

You Have:

• An advanced degree in a quantitative field such as Statistics, Economics, Computer Science, or a related discipline.
• Minimum of 2 years of experience in a data science role, with a focus on marketing science and campaign evaluation.
• Strong knowledge and practical application of statistical methods, causal inference techniques, and experimental design.
• Experience working with large datasets and proficiency in SQL, R/Python, and data visualization tools.
• Experience in the gaming industry and/or multisided marketplaces.