Staff Data Scientist at Quora

[As of June 2020, Quora has become a "remote-first" company.  This position can be performed remotely from anywhere in the world, regardless of any location that might be specified above.]
About Quora:
The vast majority of human knowledge is still not on the internet. Most of it is trapped in the form of experience in people's heads, or buried in books and papers that only experts can access. More than a billion people use the internet, yet only a tiny fraction contribute their knowledge to it. We want to democratize access to knowledge of all kinds — from politics to painting, cooking to coding, etymology to experiences — so if someone out there knows something, anyone else can learn it. Our mission is to share and grow the world's knowledge, and we're building a world-class team to help us achieve this mission.
About the Team:
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 rigor-driven 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 work to advance our culture of rational decision making.
About the Role:
As a data scientist at Quora, you'll work closely with product managers, product designers, and engineers to devise appropriate measurements and metrics, design randomized controlled experiments, build visualizations, and tackle hard, open-ended problems that uncover usage patterns and opportunities for the company. Quora has a wide range of rich data, giving you ample room for exploration and creativity. Examples of some projects our data scientists have worked on include modeling our long-term growth, improving the relevance and personalization of the homepage feed, and exploratory analysis of factors driving question-asking behavior. For more about our work, see Quora's Data blog at https://data.quora.com/.
As a staff data scientist, you will draw on your experience to excel not only in your own work but also to elevate data’s impact at a company-wide level. You will provide team mentorship that propels the work of your colleagues while helping to establish best practices for data usage across Quora.
Responsibilities:

Extract actionable insights from broad, open-ended questions
Create, design, and evaluate experiments to measure the impact of product changes
Analyze data from across the product to uncover the root causes of metric movements
Communicate data-driven results to cross-functional stakeholders to inform product decisions
Develop tools to scale and automate analyses, improving productivity across the company
Improve the work of other data scientists through mentorship and by bringing industry best practices to the team

Minimum Qualifications:


Ability to be available for meetings and impromptu communication during Quora's "coordination hours" (Mon-Fri: 9am-3pm Pacific Time).  Learn why here
5+ years work experience in an analytical or quantitative role as a Data Scientist or similar title
3+ years experience working on product analytics
Extensive experience generating insights using statistical techniques (e.g. regression, hypothesis testing)
Demonstrated ability to clearly explain data results to cross-functional teams
Experience using a procedural programming language (e.g. Python, R) to manipulate, clean, and analyze data
Ability to exercise judgment and combine quantitative skills with intuition and common sense
Experience evangelizing best practices and process improvements on your team

Preferred Qualifications:

Experience working with large data sets and distributed computing tools (e.g. Redshift, Presto)
Experience pushing code and navigating a complex codebase
Active Quora user with curiosity about the product

 
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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