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 .
The opportunity
Build the machine learning capabilities that help advertisers understand what they could achieve on Reddit and make better investment decisions.
On the Forecasting team, you will develop models that estimate how campaign outcomes could change with different budgets, bids, audiences, creative performance, or objectives. Your work will connect supply and demand forecasting, audience availability, and response prediction to help advertisers compare alternatives and identify valuable opportunities.
This is a hands-on role with end-to-end ownership of forecasting models and production capabilities. You will drive projects from problem formulation and technical design through evaluation, deployment, and iteration, working closely with engineers and cross-functional partners.
What you’ll do
• Own forecasting and scenario modeling projects. Translate advertiser questions into modeling problems involving delivery, reach, performance, and investment tradeoffs. Develop technical approaches, make practical tradeoffs, and drive execution.
• Connect inventory, demand, and response. Use signals about available advertising opportunities, audience activity, marketplace competition, and predicted response to improve estimates of achievable campaign outcomes.
• Model outcomes under alternative choices. Build and improve models that estimate the effects of changes in budget, bid, audience, or optimization objective, accounting for relevant auction dynamics and campaign constraints.
• Help advertisers identify opportunity. Incorporate predictions from partner teams, including creative-performance estimates, to evaluate potential improvements in delivery, efficiency, or advertiser value.
• Improve model generalization. Develop approaches for sparse segments, cold start, seasonality, delayed feedback, and changing marketplace conditions. Choose methods that balance predictive quality, complexity, and production requirements.
• Build trustworthy evaluations. Measure forecast accuracy, calibration, uncertainty, and performance across advertiser cohorts. Document modeling assumptions and limitations, and work with partners to determine which scenario comparisons the evidence supports.
• Close the learning loop. Compare predictions with mature outcomes, investigate systematic errors, and use experiments and observed results to improve forecasts and validate scenario estimates.
• Deliver reliable production systems. Own training, inference, monitoring, and iteration for your models. Collaborate wi