Staff Data Scientist, Causal Inference & Experimentation

Discord · San Francisco Bay Area

In short

▸Científico de datos especializado en inferencia causal y experimentación para mejorar decisiones de producto en Discord.
▸Diseñas estrategias, educas a equipos y validas métodos estadísticos para cientos de experimentos diarios.
▸Destaca por liderar el enfoque científico de la plataforma de experimentación con impacto directo en 90M usuarios diarios.

Fluent written and spoken English (required)

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What they ask for

✓Experiencia comprobada liderando plataformas de experimentación con métodos estadísticos rigurosos.
✓Doctorado en campo cuantitativo (estadística, economía, etc.) o experiencia práctica equivalente.
✓4+ años diseñando, implementando y analizando experimentos o proyectos de inferencia causal.
✓Habilidad para comunicar conceptos estadísticos complejos a audiencias técnicas y no técnicas.
✓Capacidad comprobada de crear y entregar programas de capacitación sobre experimentación e inferencia causal.
✓Dominio de Python, SQL, R o lenguajes de programación estadísticos.

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PythonSQLRAI/LLM toolingexperimentation platformscausal inferencestatistical programmingdata-driven decision makingresearchworkshops

Who should you write to at Discord?

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Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. Discord's Experimentation Platform puts data at the heart of the company's decision-making and growth - we run hundreds of experiments at any given time, and those results turn directly into business decisions across Discord. As a Staff Data Scientist on this team, you will ensure that the statistical underpinnings of our experiments 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; you will be presented with significant leadership opportunities as we evolve. Our team directly impacts the strategy and roadmaps that improve Discord for its more than 90M daily active users! If helping make Discord an even better place to hang out with your friends sounds like an exciting challenge - we'd love to chat with you! What you will be doing • Formulate the vision and set the roadmap for the future of the Experimentation Platform, in partnership with engineering, product, and data science stakeholders. • Provide statistical expertise, ensuring that experimentation methodologies and frameworks are sound and aligned with best practices in causal inference and experimental design. • Partner closely with engineering and product to improve the reliability, scalability, and adoption of experimentation across Discord - including modern AI/LLM tooling where it can accelerate rigor and speed. • Lead initiatives to educate and train cross-functional teams - including workshops, training sessions, and educational materials - on experimentation design, statistical methodology, and causal inference. • Empower Discord's Data Science team (50+ members) to adopt more rigorous causal inference methods. • Lead and conduct original causal inference research on high-priority Discord questions, in partnership with the wider Data Science team. • Engage directly with experimentation customers - data scientists, product managers, and engineers - to ensure the platform enables fast, reliable, data-driven decisions. What you should have • Proven experience leading experimentation platform work, including designing and validating statistical methodologies to ensure the accuracy and reliability of experimental results. • PhD in a quantitative field (e.g. Statistics, Economics, Political Science, Psychology) or equivalent practical experience, plus 4+ years designing, implementing, and analyzing experiments or causal inference projects. • Ability to critically evaluate and recommend statistical approaches that balance velocity and reliability across a variety of product launches. • Strong passion for education, with a track record of communicating complex statistical and experimental design concepts to technical and non-technical audiences and fostering a culture of data literacy. • 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/or other statistical programming languages. Bonus Points • Interest in conducting literature reviews, translating and championing best scientific practices across the company. • Track record using causa

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