• PhD in a quantitative field (e.g. Statistics, Economics, Political Science, Psychology, etc.) and 4+ years of experience designing, implementing and analyzing experiments or causal inference projects
• Ability to critically evaluate and recommend statistical approaches and methodologies that enhance the integrity of experimentation frameworks during platform development and rebuild phases
• Proven experience in designing and validating statistical methodologies for experimentation platforms or similar systems, with a focus on ensuring the accuracy and reliability of experimental results
• Strong passion for education and the ability to communicate complex statistical and experimental design concepts clearly and effectively to both technical and non-technical audiences
• Demonstrated experience in developing and delivering training programs or educational content related to experimentation, causal inference, or statistical analysis, with a track record of fostering a culture of data literacy within an organization
• Proficient with Python, SQL, R, and other statistical programming languages

Desirable

• As a Causal Inference Data Scientist on this team, you will ensure that the statistical underpinnings of this rebuild are sound, that experimenters are able to design experiments with high rigor, and that Discord makes the best business decisions on the basis of these experiments
• We are a small and quickly growing team; by joining us as an early team member, you will be presented with significant leadership opportunities as we evolve
• Provide statistical expertise in the rebuilding of the experimentation platform, ensuring that all statistical choices, methodologies, and frameworks are sound and aligned with best practices in causal inference and experimental design
• Collaborate closely with engineering and product teams during the platform rebuild to define and implement robust statistical methods that improve the reliability and scalability of experimentation at Discord
• Lead initiatives to educate and train cross-functional teams on best practices in experimentation design, statistical methodologies, and causal inference, ensuring a deep understanding of the principles that drive sound decision-making under uncertainty
• Develop and deliver engaging workshops, training sessions, and educational materials that demystify complex statistical concepts and promote data-driven decision-making across the company
• Empower our Data Science team (50+ members) to use more rigorous causal inference methods
• In addition to consulting within the wider Data Science team (50+ members), lead and conduct causal inference research of your own on important Discord priorities