Arik Friedman

@arikf.net

Data Scientist @ Atlassian Spent some time looking into software teams' effectiveness, and how software teams can use data to reflect and improve how they work. These days I'm trying to learn more about Statistical Process Control.

Back in MeasureCamp Sydney I had the opportunity to reflect on lessons I picked up throughout my tenure as a data scientist at Atlassian. This led to a fun discussion at the APH on what it actually means to "get things right" in data analysis.

Tim Wilson@tgwilson.bsky.social · 6mo ago

Major oopsies happen when data looks too good to be true...but we ignore our gut feeling. @arikf.net shared his hard-learned lesson about trusting intuition alongside rigorous analysis on the latest Analytics Power Hour! analyticshour.io/2026/04/28/2...

I was tagged the other day by someone kindly sharing my Python Rgonomics post and realized that my thesis of "tooling keeps improving" held up too well and some of the recos have changed Hence, here's the 2025 update: www.emilyriederer.com/post/py-rgo-... Now feat uv (vs pyenv, pdm) and Positron

Python Rgonomics - 2025 Update | Emily Riederer

Switching languages is about switching mindsets - not just syntax. New developments in python data science toolings, like polars and seaborn’s object interface, can capture the ‘feel’ that converts fr...

emilyriederer.com

Spent hours yesterday to get a SQL cell in a databricks job use a variable that was set in a prior python cell. Amazing how something that seems so trivial can be so convoluted. Is that what "business impact" looks like?

A number of artists and creators have made their home on Bluesky, and we hear their concerns with other platforms training on their data. We do not use any of your content to train generative AI, and have no intention of doing so.

Yeah, I think the immune response of "AI will replace us" was just so misguided. "AI will help us" is so much healthier. I write more code because of Cursor, not less.

The talk about "automating analysts' work" reminded me of my past attempt to run an LLM through our Data Science Interview. medium.com/atlassiandat... A colleague of mine actually repeated that recently - it's clear that LLMs got better, but they still need a human in the loop to help them along.

Will Generative AI make data scientists obsolete?

Would ChatGPT and its Code Interpret plugin pass Atlassian’s Data Science interview? How can data scientists leverage generative AI?

medium.com

“We shall spend an incredible amount of money building a data warehouse and a data science team to generate business insights. Everyone will do this.” —Sir, I assume these data teams will be trusted and their data used for important decisions “No, decisions will be made primarily on vibes”

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Hi, I'm Arik. I'm a data scientist at Atlassian, living in Sydney, Australia. I did some software engineering and product management in the past, but a PhD on Privacy Preserving Data Mining eventually led me to work with data.