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Peter Lenz

Vice President of Data Science, Near

I'm Peter (he, him), a Geographer and Data Scientist based in New York City. I combine a deep domain expertise in geoinformatics and economic geography with technical skills in programming, machine learning, NLP, among others. I'm working to create 'Big Social Science'.

Peter Lenz

Sessions / 2023 / 1 talk

  • Everything I Know About Data Science I Learned From Model Railroading

    Data scientists build models of the real world using 1s and 0s. Model Railroaders build models of the real world using plastic and metal. In the end, they’re both models and Model Railroaders have been at it way longer than we DS have. Let’s look at parallel concepts like overfitting versus the 10 foot rule, synthetic data versus prototype freelancing, or assumptions versus modeler’s license and see what lessons from other realms of model building we can bring home to DS.

Sessions / 2017 / 1 talk

  • Zip codes and other lies your map told you

    Your spatial data might be lying to you. Zip code is the most common piece of geo-data analysts and data scientists see, but it has many quirks that can derail your analysis and lead to false conclusions. We'll look at the zip code and learn exactly what it is - and what it isn't. To do this we'll take a look at how a piece of mail get from point A to point B and take very quick trip though the history of the U.S. postal system before looking at other data you can collect that may be more appropriate for spatial purposes than zip code. Then we'll turn our attention to other ways seemingly good spatial data can lie to you: trap streets and paper towns.

Sessions / 2016 / 1 talk

  • Processing Geographic Data at Internet Scale

    Spatial data is a special class of data that requires extra care and thought when working with it. We'll explore some of background concepts of geography and walk through the real world methods Dstillery uses to process, filter, and generate insights on 80 billion pieces of geographic data daily.

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