Real-Time Marketplace Surge Pricing System

Dynamic Marketplace Pricing System

Design a large-scale dynamic pricing engine for a global short-term rental platform. The system must automatically adjust daily rates for millions of listings based on real-time supply and demand, seasonality, and local events. Focus on the end-to-end ML lifecycle: specifically, how you handle low-latency price delivery, prevent data leakage in a temporal setting, manage the exploration-exploitation trade-off for optimal price discovery, and evaluate system performance using causal inference or switchback testing in a marketplace with high network effects.
LightGBMKafkaFlinkSparkRedisFeastH3Causal InferenceQuantile RegressionXGBoost
00
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Real-Time Marketplace Surge Pricing System

Design a high-scale dynamic pricing system for a global ride-sharing platform. The system must process millions of real-time events to calculate surge multipliers at a granular geographic level (e.g., H3 hexagons). Focus on the end-to-end ML lifecycle: from streaming data ingestion and spatial-temporal feature engineering to a low-latency serving architecture. Address specific marketplace challenges such as feedback loops, switchback testing for online evaluation, and maintaining marketplace equilibrium under extreme demand volatility.
LightGBMXGBoostH3Apache FlinkKafkaRedisSparkPID ControllerSwitchback TestingSHAP
10
Read
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