What’s It Like to Be a Data Scientist at Quora

The role of a data scientist at Quora is multifaceted, involving a range of intriguing and impactful tasks. Joining the team in late December, I was part of a three-person data intelligence division, collaborating closely with Yair Livnen and Matyas. Our mission is to gather, understand, and disseminate insights about Quora usage, a truly dynamic and ever-evolving task.

Insights into Quora Usage

A significant part of our role involves delving into the metrics that underpin Quora's growth and functionality. During my early days on the job, I investigated why certain topics gained immense traction while similar ones struggled. This required a thorough analysis of various factors, including user habits, external events, and in-house initiatives. This kind of investigative work not only helps us pinpoint patterns but also informs future strategies.

Data Science at Quora

Life as a data scientist at Quora is anything but routine. We are deeply involved in both the analysis and the engineering side of the platform. From the analytics of user behavior to the engineering of infrastructure, our work spans the entire scope of the company. Here’s what a typical day looks like for us:

Analyzing Metrics: We continuously monitor key metrics to gauge the health and growth of topics and the platform as a whole. Tools like dashboards help us make informed decisions based on real-time data. A/B Testing: We frequently run A/B tests to refine our user experience. A recent example involved the integration with Facebook Timeline, where we monitored the results to ensure the best possible user experience. Modeling: Yair has been continuously improving the models related to the feed, making minor but significant adjustments to enhance engagement. Email Digests: Matyas has been working tirelessly to optimize the weekly digest emails, ensuring users get the most valuable information from Quora. Engineering Improvements: We work on a wide range of engineering tasks, from interfacing with Hive and R applications to implementing more efficient logging and data sharding techniques. Exploratory Data Analysis: Each of us has a bit of free time to work on unique data projects. These projects take off when you have a structured, curated, and moderated dataset combined with natural language processing. The possibilities are endless, from sentiment analysis to personalized recommendations.

Understanding the Role

The data scientist role at Quora is not just about crunching numbers; it's about making a tangible impact on how the platform functions and grows. Our task is to translate data into actionable insights that drive the company's strategic decisions. From growth hacking to user experience improvements, the responsibility is immense.

Conclusion

To be a data scientist at Quora is to be part of something bigger than just a job. It’s about shaping a platform that connects people from all over the world. The challenges are immense, but the potential reward is equally great. If you have a passion for data and a knack for turning insights into innovative solutions, Quora might just be the place for you.