Jeremy Stanley
San Francisco, California, United States
3K followers
500+ connections
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Data science, machine learning and AI leader. Deep domain expertise in logistics…
Articles by Jeremy
Activity
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The Anomalo team just returned from a highly productive and energizing company onsite in Chicago! Our team gathered to start the second half of the…
The Anomalo team just returned from a highly productive and energizing company onsite in Chicago! Our team gathered to start the second half of the…
Liked by Jeremy Stanley
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Databricks announced yesterday that Anomalo is their Emerging Partner of the Year!!! In our press release, Tim Ng, the data products engineering…
Databricks announced yesterday that Anomalo is their Emerging Partner of the Year!!! In our press release, Tim Ng, the data products engineering…
Shared by Jeremy Stanley
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What does it take to punch above your weight with Databricks, the fastest-growing data company on the planet? A great product, awesome customers…
What does it take to punch above your weight with Databricks, the fastest-growing data company on the planet? A great product, awesome customers…
Liked by Jeremy Stanley
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Publications
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Deep Learning with Emojis (not Math)
tech.instacart.com
Sorting shopping lists at Instacart with deep learning using Keras and Tensorflow.
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Doing Data Science Right - Your Most Common Questions Answered
First Round Review
In this article, we've summarized the advice we give to founders who are interested in building data science teams. We explain why data science is so important for many startups, when companies should begin investing in it, where to put data science in their organization and how to build a culture where data science thrives.
Other authorsSee publication -
Data Science at Instacart
tech.instacart.com
Instacart is an e-commerce marketplace, a complex last-mile logistics engine, and a dynamic source of work for personal shoppers. Data science plays a key role in our success in each endeavor. This article covers the key challenges we are tackling with data science, how we've integrated data science into engineering, and the cultural traits we look for when building the team.
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Why I Joined Instacart
Medium
Why I joined Instacart - love the product, amazing data science challenges and a humble culture.
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How to Consistently Hire Remarkable Data Scientists
First Round Review
Data science leaders are seeking fundamentally better ways to evaluate talent. In this article, I describe a new process I adapted to hire great data science talent efficiently and confidently. I describe the limitations of existing hiring approaches, the key goals this process seeks to improve, the underlying principles it is based upon and then I walk through the implementation we have experimented with at Sailthru.
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Machine Learning at Scale
It takes skill to build a meaningful predictive model even with the abundance of implementations of modern machine learning algorithms and readily available computing resources. Building a model becomes challenging if hundreds of terabytes of data need to be processed to produce the training data set. In a digital advertising technology setting, we are faced with the need to build thousands of such models that predict user behavior and power advertising campaigns in a 24/7 chaotic real-time…
It takes skill to build a meaningful predictive model even with the abundance of implementations of modern machine learning algorithms and readily available computing resources. Building a model becomes challenging if hundreds of terabytes of data need to be processed to produce the training data set. In a digital advertising technology setting, we are faced with the need to build thousands of such models that predict user behavior and power advertising campaigns in a 24/7 chaotic real-time production environment. As data scientists, we also have to convince other internal departments critical to implementation success, our management, and our customers that our machine learning system works. In this paper, we present the details of the design and implementation of an automated, robust machine learning platform that impacts billions of advertising impressions monthly. This platform enables us to continuously optimize thousands of campaigns over hundreds of millions of users, on multiple continents, against varying performance objectives.
Other authorsSee publication -
A Viewability Technology Primer, Part 2: Vendor Selection & Applications
AdExchanger
Guidance on the selection of a viewability technology provider, and a summary of recommended applications of viewability data for both brand and direct response advertisers.
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A Viewability Technology Primer Part 1: Promises & Pitfalls
AdExchanger
A summary of the six primary technologies used in measuring viewability today, along with strengths and weaknesses: page geometry, panel, behavioral proxy, browser exploits, publisher API and browser monitoring.
Patents
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System and method for appying data modeling to improve predictive outcomes
Filed US US 14/984,634
For predicting future user behavior and tailoring interventions based on predicted outcomes.
Other inventorsSee patent
Projects
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tidyjson
A library for turning arbitrarily nested data in JSON format into tidy tables for downstream analytics or machine learning applications in R.
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