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Principal Data Scientist, User Ecosystem

AI Summary
Reddit is hiring a principal-level data scientist to set scientific strategy for its consumer ecosystem, including discovery, relevance, personalization, retention, content, and communities. The role leads measurement, modeling, and experimentation for complex interactions among users, content, and communities over time. It requires deep expertise in machine learning, causal inference, behavioral modeling, and large-scale consumer-product experimentation. The successful candidate will influence Product, Engineering, Research, and Community leaders while mentoring other scientists. This is a US-remote senior individual-contributor leadership role with a disclosed annual base-salary range of $313,000 to $365,100 USD.
Remote from
USA
Salary
USD 313k–365,100 / yr
Employment
Full Time
Experience
Senior
Published
Apply before
8 Dec 2026
Listing views
33
Application actions
3
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Opportunity details

About this role.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is a complex consumer ecosystem where users, content, communities, and conversations interact over time. We are looking for a very senior data science thought leader to shape how Reddit understands and improves that ecosystem for the user / consumer flywheel.

This role will define the measurement, modeling, and experimentation strategy for major Consumer questions: how users discover value, form habits, and deepen engagement; how we understand and serve user intent; how content and communities evolve; and how our systems create durable value for users, contributors, communities, and Reddit.

The ideal candidate will bring deep expertise in one or more areas of consumer science, such as:

  • Recommender systems and information retrieval
  • User modeling, personalization, lifecycle, LTV, or optimization
  • Content, community, or ecosystem modeling
  • Knowledge graphs and representations of users, content, and communities
  • Causal inference, experimentation, and long-term consumer measurement

You will partner with leaders across Product, Engineering, Research, and Community to turn ambiguous consumer problems into clear scientific questions, durable analytical systems, and decisions that improve Reddit at scale.

What you’ll do

  • Set the scientific direction for high-impact Consumer problems spanning discovery, relevance, personalization, user growth, retention, content, and communities.
  • Build a durable understanding of users, their intent, their needs, and the behaviors that lead to lasting value
  • Develop models and frameworks that represent users, content, communities, and their relationships over time for use in systems that operate at scale
  • Determine how to measure consumer and ecosystem health when objectives compete and short-term engagement may differ from long-term value.
  • Set learning agendas and steer experimentation strategy to distinguish durable improvement from temporary metric movement.
  • Build state-of-the-art measurement systems to evaluate heterogeneous effects across user personas, acquisition cohorts, platforms, content types, and community stages, and guide their actionability in production environments
  • Ensure coherence around ecosystem interactions including feedback loops, selection effects, interference, distribution shift, content supply, and other ecosystem risks.
  • Translate complex technical findings into clear product and business decisions.
  • Develop exceptional scientists through mentoring and influence data science org health and direction

Requirements

  • Deep expertise in at least one relevant area, with the breadth and curiosity to work across adjacent domains.
  • A deep understanding of how to model and optimize systems involving users, content, communities, and feedback loops.
  • Ability to frame and lead the most ambiguous questions, identify the most important uncertainties, and develop a rigorous path from evidence to action.
  • Exceptional technical judgment across model design, objective selection, validation, experimentation, and production tradeoffs.
  • Advanced knowledge of modern machine-learning methods for behavioral and content data, including representation learning and sequential or contextual models. Experience with deep-learning frameworks such as PyTorch or JAX.
  • Experience working across Product, Engineering, Research, and other partner teams.
  • Excellent written and verbal communication, with the ability to influence senior stakeholders and explain technical ideas clearly.
  • Significant experience applying data science, machine learning, statistics, experimentation, or causal inference to complex consumer products.

Pay Transparency:

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:

$313,000—$365,100 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

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

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThe position owns ambiguous, high-impact scientific questions in a large consumer ecosystem where feedback loops, selection effects, and long-term outcomes complicate evaluation. It demands principal-level technical judgment and substantial cross-functional influence.

Salary analysis

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

Estimated job median (per year)Market rate
$339,050
US market range (per year)$300k–$410k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a base salary range of $313,000–$365,100 USD per year; the midpoint is $339,050 annually. Estimated US market base pay for a principal data scientist leading consumer machine-learning, experimentation, and ecosystem measurement is approximately $300,000–$410,000 annually, excluding equity and other incentives.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you distinguish a durable improvement in user value from a short-term increase in engagement?

I would define a causal measurement framework that includes leading engagement metrics alongside longer-horizon retention, satisfaction, content-quality, and community-health outcomes. I would use appropriately powered experiments, cohort analysis, and follow-up measurement to test whether observed gains persist and to identify delayed or heterogeneous effects.

How would you model interactions among users, content, and communities on a platform such as Reddit?

I would start with a representation of the ecosystem as a dynamic graph, combining user behavior sequences, content features, community context, and temporal interactions. The model choice would depend on the decision use case, but I would validate it against predictive performance, calibration, causal usefulness, and potential feedback-loop risks.

Describe how you would approach an ambiguous question about declining user retention.

I would first decompose retention by acquisition cohort, user persona, platform, community exposure, and lifecycle stage to identify where the decline is concentrated. Then I would formulate competing hypotheses, assess data quality and selection effects, and prioritize experiments or quasi-experimental analyses that can distinguish correlation from causal drivers.

What risks should be considered when deploying a personalization model in a community ecosystem?

Key risks include filter bubbles, unequal exposure, content-supply effects, interference between users, community-level externalities, distribution shift, and optimization toward short-term engagement at the expense of long-term value. I would establish guardrail metrics, run controlled rollouts, and monitor outcomes across affected user and community segments.

How do you communicate a complex causal or modeling result to senior product leaders?

I lead with the decision, the estimated impact, uncertainty, and recommended action rather than technical detail. I use clear visuals and plain language to explain assumptions, limitations, and tradeoffs, while making the underlying methodology available for technical stakeholders who need deeper scrutiny.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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