A/B Testing, Staffing and Workflows

The Kinds of Data Scientist

Harvard Business Review

NOVEMBER 6, 2018

In slightly bigger teams, each of these may be a role staffed by one or more individuals. Data infrastructure: data ingestion, availability, operations, access, and running environments to support workflows of data scientists. Here are five key areas that contribute to data science operations. e.g. running Kafka and a Hadoop cluster.

Engineering

Engineering Workflows Software User Experience

How to build a growth team – lessons from Uber, Hubspot, and others (50 slides)

Andrew Chen

NOVEMBER 13, 2018

There’s a long laundry list of skills that are critical, but not often considered core to the product: adtech integrations, signup funnel A/B testing, optimizing notification delivery, testing price points, testing cohort curves, etc. This can work, but then the team needs to be staffed properly.

A/B Testing

A/B Testing Engineering User Experience Marketing

OrgDev Digest

The Kinds of Data Scientist

How to build a growth team – lessons from Uber, Hubspot, and others (50 slides)

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