The Netflix TechBlog

MARCH 2, 2021

At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group.

Analytics 207

Analytics C++ Innovation Engineering 207

The Netflix TechBlog

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

O'Reilly

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Software architecture, infrastructure, and operations are each changing rapidly. Also: infrastructure and operations is trending up, while DevOps is trending down.

Software Architecture 134

Software Architecture DevOps Data Engineering Architecture 134

The Netflix TechBlog

SEPTEMBER 10, 2019

Our A/B tests range across UI, algorithms, messaging, marketing, operations, and infrastructure changes. Due to compression and high performance computing, scientists can analyze billions of rows of raw data on their laptops using languages and statistical libraries they are familiar with like Python and R.

Metrics 215

Metrics Architecture Infrastructure Innovation 215