
Senior Staff Data Scientist - Consumer Experimentation
About this role
Role Overview
The Senior Staff Data Scientist - Consumer Experimentation position at Reddit is a senior technical leadership role focused on solving complex causal inference and experimentation challenges across the Consumer organization. This remote, United States-based position suits an expert statistician or quantitative researcher who wants to shape product strategy and experimentation rigor at a massive digital scale.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
About the Company
Reddit is a community of communities built on shared interests, trust, and authentic human conversations. Featuring over 100,000 active communities and approximately 126 million daily active unique visitors, the platform is one of the largest information sources on the internet. Reddit is committed to providing an equal opportunity workplace and reasonable accommodations for qualified individuals with disabilities.
How to Apply
Interested candidates should apply directly on the official Reddit careers page.
Skills and tech stack
Questions candidates ask
What qualifications are needed for this role?
Candidates need either a Ph.D. with 8+ years of industry experience or an M.S. with 12+ years of industry experience in applied science, data science, or experimentation roles, specifically focused on causal inference and experimental methodology.
Is this position remote?
Yes, this is a remote position based in the United States.
What is the salary range for the Senior Staff Data Scientist position?
The base salary range is $232,500 to $325,500 USD, and the role is also eligible for equity in the form of restricted stock units.
What technical skills are required?
The role requires expert knowledge of SQL, proficiency in R and/or Python, and deep expertise in causal inference and experimental design.
What are the main responsibilities of the job?
Responsibilities include serving as the technical authority on experimentation methodology, solving complex network interference and causal inference problems, building self-serve experimentation tools, mentoring data scientists, and influencing product strategy.