Topic
Data Science
All Topics
A/B Testing (9) API (1) Artificial Intelligence (31) Automation (6) Automattic (20) best practices (10) Bias in AI (6) Books and Reading (6) Career and Professional Development (14) Causal Inference (1) Communication (14) Conferences and Events (5) Data Analytics (23) Data Discoverability (4) Data Engineering (12) Data Ethics (10) Data Products (1) Data Science (53) Data Speaker Series (4) Data Visualization (23) Deep Learning (3) Distributed Work (8) Diversity and Inclusion (8) Elasticsearch (8) Experimentation (12) Information Retrieval (6) Learning and Education (6) Machine Learning (43) Marketing Analytics (7) Meetup (2) Natural Language Processing (6) Network Analysis (8) Open Source (7) Productivity (10) Python (8) Remote Work (21) Scientific Communication (10) Semantic Search (2) Social Media Analytics (1) Software Engineering (4) Surveys and Research Methods (1) Tech Industry (14) Technology Trends (1) Time Series Analysis (2) Transparency in Data (2) WordPress (21) WordPress.com (1) Work Life Balance (6)
-
ExPlat: Automattic’s Experimentation Platform
Over the past 18 months, the Decision Science team has been building the Experimentation Platform (ExPlat): a tool to help our colleagues run experiments to improve customer experiences, inform product […]
-
SQL — a Common Language for the Whole Data Team
Today, I wanted to share how we’ve empowered colleagues outside the data engineering team to write their own data transformations by overcoming coding language barriers. Within our Data team, there […]
-
“I found a lot of new and exciting ways to break WordPress.com”: Highlights of our time at Automattic
A few of my colleagues — with tenures at Automattic from just a few months to many years — share their highlights of working here. Robert Felty Robert, you rejoined us […]
-
Teaching Python to Beginners
Vicki Boykis shares some tips on how to teach beginners to code.
-
Five Paths to Automattic
Greg, Anna, Anand, Anna, and Robert — who come from a variety of backgrounds ranging from fullstack software development to linguistics, hardcore math, and more — share how they came to work with data at Automattic.
Data for Breakfast 