Speaker: Dave Press

Data Science Manager @Airbnb

Dave is a data scientist working on Trust and Risk at Airbnb. He focusses most on financial fraud and offline risk. Prior to joining Airbnb he worked in healthcare and hardware.

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Talk : Optimizing Fraud Model Thresholds @Airbnb

Tracks

  • Deep Learning Applications & Practices

    Deep learning lessons using tooling such as Tensorflow & PyTorch, across domains like large-scale cloud-native apps and fintech, and tacking concerns around interpretability of ML models.

  • Predictive Data Pipelines & Architectures

    Best practices for building real-world data pipelines doing interesting things like predictions, recommender systems, fraud prevention, ranking systems, and more.

  • ML in Action

    Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud

  • Real-world Data Engineering

    Showcasing DataEng tech and highlighting the strengths of each in real-world applications.