[Hiring] Principal Data Scientist @Reddit

Role Description

Reddit is looking for a very senior data science thought leader to shape how Reddit understands and improves its consumer ecosystem. This role will define the measurement, modeling, and experimentation strategy for major Consumer questions, including:

• How users discover value, form habits, and deepen engagement
• Understanding and serving user intent
• How content and communities evolve
• Creating 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.

Qualifications

• 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.

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.

Benefits

• Base salary range: $313,000 — $365,100 USD
• Eligible to receive equity in the form of restricted stock units
• 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
• Parental leave