I’ve been thinking a lot lately about Engineering Leadership. This is a very difficult job for all the reasons that leadership is difficult, management is difficult and that software development is a difficult discipline. For various reasons – we as a species suck at writing software. Writing great software is HARD. Nevertheless we as a… Continue reading Engineering Leadership: Lessons from Rugby
Author: Peadar Coyle
I help organisations understand, assess and execute on emerging opportunities in data science and machine learning. I've helped organisations from startups to larger organisations unlock value from their data in verticals such as Supply Chain Management, Advertising and Financial Services. I am happiest at the intersection of product, data science and engineering. My work has exposed me to working with sales people, legal (GDPR), risk and various other functions or cross-functional teams.If you're looking for a data scientist for some advisory work or technical due diligence, if you have a project in mind or are looking for me to do some writing or speaking, feel free to get in touch [email protected]
Friday wins – celebrating shipping and delivery
More meetings? At Aflorithmic we recently have been experimenting with Friday Wins. It’s important in a startup to enable the company to build things and talk to customers. This matters a lot to ‘building something people want’. However, I wanted to talk a bit about a meeting style that I’ve found that works pretty well,… Continue reading Friday wins – celebrating shipping and delivery
Why building ML systems is about more than ML?
I’m going to use a bit of a click bait title for this article. But the aim of this article is to share experiences I’ve gathered from about 10 years building ML systems, and building ML teams. Why ML is about more than ML I saw the following tweets by Erik so I’ve added them.… Continue reading Why building ML systems is about more than ML?
Migrations – or how to fix technical debt
My company http://www.aflorithmic.ai recently went through some migrations. There were a few from the easy – moving from python anywhere to AWS Elastic Beanstalk, to the more involved – a big refactoring that involved moving ejecting from Expo. However, I think the lessons apply. Firstly, I’m not an expert. I’ve been involved in migrations… Continue reading Migrations – or how to fix technical debt
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How can Data Scientists survive layoffs?
Disclosure: I’m not really a data scientist these days, I’m a founder of a tech startup (which has a core AI component). These are my unfair, biased, and prejudiced views based on experience of being a professional data scientist for something like a decade. So firstly, I think it’s worth declaring that machine learning and… Continue reading How can Data Scientists survive layoffs?
Synthetic Media – What’s coming next?
What is synthetic media? Synthetic Media includes artificially-generated video, voice, images or text, where AI takes on part (or all) of the creative process. This falls under the broader landscape of synthetic, artificial or virtual reality (photo-realistic AR/VR). One of the more powerful things about modern machine learning or AI methods is that they can… Continue reading Synthetic Media – What’s coming next?
The rise of the creator class
Unbundling of people or ‘rise of the creator class’ If you work in Tech you end up exposed to trends, and if you’re a product-focused engineer you think a lot about ‘product’, product strategy and what’s ‘coming next’. One question in our current ecosystem is ‘what’s next after marketplaces’ we’ve already seen very successful companies… Continue reading The rise of the creator class
Data Science for Decision Support: Or why Bayesian Analysis matters
One of the distinctions I like to make about modern ‘Data Science’ is between ‘data science for decision support’ and ‘machine learning’. h Basically speaking machine learning, which is often product-focused – is generally something like ‘there’s this problem in fraud, credit scoring’ and we need an automated and deployed system. You’ll often work super… Continue reading Data Science for Decision Support: Or why Bayesian Analysis matters
The two kinds of work in Software Products
I’ve been working on software products for several years now. And while a lot of my work has been greenfield, I’ve struggled to articulate the different kinds of work that happens in product development. Des Traynor one of the founders of Intercom had a great talk about this. (Source: Video) Often people don’t understand the two… Continue reading The two kinds of work in Software Products