Data Scientist Quora positions focus on delivering results in their domain. This page aggregates open Data Scientist Quora roles and what employers typically expect.
[Quora is a privately held, "remote-first" company https://www.quora.com/q/quora/Remote-First-at-Quora. This position can be performed remotely from multiple countries around the world. Please visit careers.quora.com/eligible-countries http://careers.quora.com/eligible-countries for details regarding employment eligibility by country.] ABOUT QUORA: Quora’s mission is to grow the world's collective intelligence. To do so, we have two platforms: - Quora http://quora.com: a global knowledge sharing platform with over 300M monthly unique visitors, bringing people together to share insights on various topics and providing a unique platform to learn and connect with others. - Poe https://poe.com/: a platform providing millions of global users with one place to chat, explore and build with a wide variety of AI language models (bots), including GPT-5.6-Sol, Claude-Opus-5, Claude-Fable-5, Claude-Sonnet-5, Kimi-K3, and thousands of others. As AI capabilities rapidly advance, Poe provides a single platform to instantly integrate and utilize these new models. Behind these products are passionate, collaborative, and high-performing global teams. We have a culture rooted in transparency, idea-sharing, and experimentation that allows us to celebrate success and grow together through meaningful work. Join us on this journey to create a positive impact and make a significant change in the world. This role will be working on our Quora product. ABOUT THE TEAM AND ROLE: The Data Team is highly empowered at Quora, helping navigate complexity and influencing product and company strategy directly. Quora's outsized commitment to data is visible in everything we do, from our sophisticated experimentation processes to the backgrounds of our leaders. With this emphasis on data and empirics, we aim to balance rigor and pragmatism, searching for scrappy solutions in pursuit of our mission. In joining Quora's strong data team, you'll both benefit from and help advance our culture of rational decision making. As a member of our team, you'll work closely with product managers, product designers, engineers, and other cross-functional partners to devise appropriate measurements and metrics, design randomized controlled experiments, build visualizations, and tackle hard, open-ended problems that uncover usage patterns and opportunities across Quora. Quora has a wide range of rich data, giving you ample room for exploration and creativity. Data scientists at Quora work across multiple domains, including user growth, content quality, monetization, personalization, marketplace dynamics, and long-term company strategy. Example projects include modeling long-term growth, improving the relevance and personalization of the homepage feed, analyzing drivers of user engagement and question-asking behavior, optimizing marketplace efficiency, and evaluating the effectiveness of monetization initiatives. RESPONSIBILITIES: - Own well-scoped, impactful problem spaces across product and business domains — from framing the question, to conducting the analysis, to working with cross-functional partners to implement solutions - Design and evaluate experiments to measure the impact of product and strategic changes - Analyze data from across the product to uncover root causes of metric movements - Partner with cross-functional stakeholders to inform product decisions with data - Contribute to tools, methodologies, and frameworks that help make the data team and the company as a whole smarter about data MINIMUM REQUIREMENTS: - Availability for meetings and impromptu communication during Quora's “coordination hours https://quora.com/coordination_hours" (Mon-Fri: 9am-3pm Pacific Time) - 2+ years work experience in an analytical or quantitative role, including 1+ as a Data Scientist or similar title - Demonstrated ability to independently drive data analyses that inform product or business decisions - Proficiency with statistical techniques (e.g. regression, hypothesis testing, causal…