R

Reddit

Runs online communities for discussion and advice

Senior Staff Applied Scientist - Science Platform

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • A doctorate in Statistics, Economics, Computer Science, Applied Mathematics, Operations Research, or a related discipline, or a master’s degree supported by comparable depth of expertise.
  • At least eight years of relevant industry work following a doctorate, or ten years with a master’s degree, in applied science, data science, scientific software development, or related roles.
  • Deep knowledge of statistical inference and econometrics, with practical experience developing causal methods for observational data and evaluating the assumptions that make their conclusions credible.
  • Experience developing and deploying forecasting systems, including time series modeling, temporal validation, prediction intervals, and assessment of performance as underlying conditions change.
  • Strong software engineering skills, including substantial experience writing and maintaining production Python software; familiarity with API design, automated testing, code review, version control, and operational monitoring.
  • Ability to critically assess scientific literature, reproduce relevant findings, and turn promising methods into reliable software that solves practical problems.
  • Experience developing LLM applications or analytical agents, including tool use, code execution, and systematic evaluation of their outputs.
  • Ability to communicate statistical assumptions, uncertainty, and technical tradeoffs to business audiences.
  • Experience developing other technical contributors through mentorship, design reviews, and collaboration across organizational boundaries.
  • Ability to make progress on ambiguous problems, prioritize consequential work, and deliver useful capabilities through rapid iteration.

Responsibilities

  • Define the scientific roadmap for Data Science Platform across agentic analytics, causal inference, and forecasting, identifying opportunities where advances in methodology can improve decision-making at scale across Reddit.
  • Research, evaluate, and implement emerging methods; move from research papers to working prototypes, validate their practical value, and develop successful approaches into maintained production capabilities.
  • Design and build the analytics agent’s architecture and capabilities, including how it decomposes questions, selects scientific methods, uses data and analytical tools, checks assumptions, and produces reproducible results.
  • Build reusable causal inference tools that help teams estimate the effects of product changes, policies, and business decisions using observational data.
  • Develop shared forecasting capabilities for business and product metrics, including probabilistic predictions, hierarchical forecasts, and scenario analysis.
  • Create evaluation frameworks to measure the correctness and usefulness of agent-generated analyses; build benchmarks, simulations, and automated checks that detect methodological errors, unsupported claims, and misleading interpretations.
  • Own implementation of scientific methods in production software by writing robust Python code and partnering with engineers on libraries, APIs, data pipelines, observability, and system design.
  • Work with data scientists and business partners to identify recurring analytical needs and translate them into accessible platform capabilities, documentation, and workflows.
  • Influence technical and organizational strategy through scientific recommendations, mentor scientists and engineers, and share methodological advances internally and externally where appropriate.

Desired Qualifications

  • Publications, open-source contributions, or widely adopted internal tools in agentic analytics, causal inference, forecasting, or related fields.
  • Experience building scientific libraries or platforms used by other data scientists, including interfaces that make sophisticated methods accessible to people with different levels of statistical expertise.
  • Experience building agents at scale that perform substantive analytical work, including retrieval of relevant data and context, selection of methods, execution of Python or SQL, and validation of findings.

About the Company

Reddit

Runs online communities for discussion and advice

Reddit runs a website and mobile app where people discuss interests, ask questions, share links, and post photos or videos. Its user-created communities, called subreddits, cover topics from news and entertainment to hobbies, local recommendations, and technical help. People reply in comment threads and vote posts or comments up or down, affecting which discussions appear prominently in each community and on their feeds. Reddit earns most of its revenue from advertising, while its Reddit Pro tools help businesses and publishers share content and track conversations about their brands. Reddit was founded in 2005 and is headquartered in San Francisco, California.

Company size
1,001-5,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2005

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