[All remote jobs](https://jobicy.com/jobs.md)Open role[![Quora logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2020/09/WRILS-200916172339-629302.jpg)](https://jobicy.com/company/quora.md)Remote opportunity at[Quora](https://jobicy.com/company/quora.md)

# Data Scientist – Quora

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

[Apply for this job](#job-application)[View company](https://jobicy.com/company/quora.md)Share29 Aug 2026Published50Listing views3Application actions28 Sep 2026Apply before  Opportunity details

## About this role.

AI SummaryThis Data Scientist role supports Quora's product organization through product analytics, experimentation, metric design, and strategic problem solving. The hire will independently scope analyses, investigate metric changes, design randomized controlled experiments, and partner with product, design, and engineering stakeholders. Required capabilities include statistical inference, causal thinking, Python or R, and clear communication of analytical conclusions to nontechnical partners. The work spans growth, content quality, personalization, monetization, marketplace dynamics, and long-term strategy in a remote-first environment with Pacific Time coordination hours. It is a mid-level individual-contributor role requiring at least two years of quantitative experience, including one year as a data scientist or comparable professional.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

4/5EasyHard

### Pace & Pressure

4/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThe role combines rigorous statistical work with ambiguous product questions, requiring the candidate to independently frame problems and convert findings into decisions. Its cross-functional scope and expectation to own impactful problem spaces make it more demanding than a purely reporting-focused analytics role.

## Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianHighly competitive$147,559US market range$110k–$185k0$204k

AI insightThe disclosed US annual base-salary range is $122,000 to $173,117 USD, with a midpoint of $147,558.50. A reasonable US market estimate for a mid-level product data scientist with experimentation and causal-inference responsibilities is approximately $110,000 to $185,000 annually; equity and benefits are additional and are not included in the base-pay range.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Product analytics](https://jobicy.com/jobs?search_keywords=Product%20analytics.md)[A/B testing](https://jobicy.com/jobs?search_keywords=AB%20testing.md)[Randomized controlled trials](https://jobicy.com/jobs?search_keywords=Randomized%20controlled%20trials.md)[Statistical inference](https://jobicy.com/jobs?search_keywords=Statistical%20inference.md)[Causal inference](https://jobicy.com/jobs?search_keywords=Causal%20inference.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[R](https://jobicy.com/jobs?search_keywords=R.md)[Data visualization](https://jobicy.com/jobs?search_keywords=Data%20visualization.md)[SQL and distributed data tools](https://jobicy.com/jobs?search_keywords=SQL%20and%20distributed%20data%20tools.md)[Cross-functional communication](https://jobicy.com/jobs?search_keywords=Cross-functional%20communication.md)

Sample interview questionsDescribe an experiment you designed to evaluate a product change. How did you choose success metrics?I begin with the user and business hypothesis, define a primary metric directly tied to the intended behavior, and add guardrail metrics for quality, retention, or unintended effects. I determine the unit of randomization, calculate sample-size requirements, validate instrumentation, and interpret results with confidence intervals and practical impact rather than relying on a p-value alone.

A key engagement metric declines unexpectedly. How would you investigate the root cause?

I would first validate the metric definition and data pipeline, then decompose the change by platform, geography, acquisition channel, cohort, and key product surfaces. I would align the timing with launches, incidents, and seasonality, identify where the contribution to the decline is concentrated, and use targeted analyses or follow-up experiments to distinguish correlation from likely causes.

How do you explain a causal-inference result to a nontechnical product partner?

I state the decision question first, explain the comparison group and why it provides a credible baseline, and translate the result into expected user and business impact. I clearly communicate uncertainty, assumptions, and limitations, then recommend a concrete next step such as rollout, iteration, or collecting more evidence.

How would you evaluate a recommender-system improvement before and after launch?

Offline, I would assess ranking and relevance measures on representative data while checking segment performance and potential bias. Online, I would run a controlled experiment with engagement and satisfaction metrics as primary outcomes, retention and content-quality measures as guardrails, and monitor for novelty effects or adverse marketplace impacts before making a rollout decision.

Tell us about a time you handled an open-ended analytical problem with limited direction.

I structure ambiguity by clarifying the decision to be made, documenting assumptions, and creating a small initial analysis that quickly tests the highest-value hypotheses. I share intermediate findings with stakeholders, refine the scope based on evidence, and deliver a recommendation with clearly stated tradeoffs, confidence level, and follow-up measurement plan.

[[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:

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[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.

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[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:

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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

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Design and evaluate experiments to measure the impact of product and strategic changes

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Analyze data from across the product to uncover root causes of metric movements

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Partner with cross-functional stakeholders to inform product decisions with data

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Contribute to tools, methodologies, and frameworks that help make the data team and the company as a whole smarter about data

### Minimum Requirements:

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Availability for meetings and impromptu communication during Quora’s “[coordination hours](https://quora.com/coordination_hours)” (Mon-Fri: 9am-3pm Pacific Time)

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2+ years work experience in an analytical or quantitative role, including 1+ as a Data Scientist or similar title

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Demonstrated ability to independently drive data analyses that inform product or business decisions

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Proficiency with statistical techniques (e.g. regression, hypothesis testing, causal inference) and their practical application

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Effective communication skills, including the ability to translate business needs into analytical questions and to explain technical results to cross-functional partners

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Experience using a procedural programming language (e.g. Python, R) for data manipulation, modeling, and analysis; comfort working in a production codebase

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Strong judgment that blends quantitative rigor with product intuition and common sense

### Preferred Requirements:

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Experience evaluating experiments or recommender systems in offline analysis and online experiments

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Experience with large data sets and distributed computing tools (e.g. Presto/Trino)

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Active Quora user with curiosity about the product

At Quora, we value diversity and inclusivity and welcome individuals from all backgrounds, including marginalized or underrepresented groups in tech, to apply for our job openings. We encourage all candidates who share a passion for growing the world’s knowledge, even those who may not strictly meet all the preferred requirements, to apply, as we know that a diverse range of perspectives can have a significant impact on our products and our culture.

### Additional Information:

We are accepting applications on an ongoing basis. This role is a backfill for an existing vacancy.

Quora offers a wide range of benefits including medical/dental/vision coverage, equity refreshers, remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are country-specific and may vary.

There are many factors that will determine the starting pay, including but not limited to experience, location, education, and business needs.

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US candidates only: For US based applicants, the salary range is $122,000 – $173,117 USD + equity + benefits.

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Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $156,650 – $177,828 CAD + equity + benefits. For all other locations in Canada, the salary range is $146,206 – $165,972 CAD + equity + benefits.

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.

AI technology may assist in sorting applications and recording interview notes, but all decisions are made by a member of our team.

To ensure a secure hiring process, all final candidates will undergo identity verification and a comprehensive background check prior to onboarding.

Job Applicant Privacy Notice: [https://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice](https://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice)

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