Vermin2000

National Association of Realtors | Chicago or Washington DC - ONSITE | Data Analyst | Full Time

We want Python + Pandas, SQL, statistics, data visualization and some AI; the usual data science stack. Job is in-depth data analysis across multiple data sets - the challenges change weekly. We're using Cursor for data science and AI is permeating all our analysis work - we're transforming from traditional data science to being AI-forward.

Job is here: https://realtors.applicantstack.com/x/detail/a2yfvt49zurx

Data analyst | Chicago, IL or Washington DC only| No visa sponsorship

National Association of Realtors is hiring a data analyst to work with customer data and to work on AI-enabled projects. We're looking for Python and SQL with some stats.

I'm the hiring manager.

Please apply on the site: https://realtors.applicantstack.com/x/detail/a2yfvt49zurx

Some ways of getting into space from the earth.

Different ways of getting to space and a view of how likely/mature they are.

British Army runs a war game in a disused part of a tube station in central London.

Some musings I had on what life would be like inside a rotating space habitat.

I had trouble getting a Ralph loop going, so I've written some notes in the hope they'll help other people get started faster.

Some thoughts on the novel: its strengths and weaknesses, why it's so different from other first contact novels. I'd love to hear people's views of the novel.

New trains for Amtrak in the US. Better than before, but still a long way behind the best in Europe and Asia. The manufacturing process seems crazily manual.

A blog post about what it was, how it worked, and the controversy surrounding it. It's a key piece of the modern AI story, but also a cautionary tale.

Some thoughts on why AI-assisted learning of APIs doesn't really work and why it's better to hand code stuff if you're learning. Love to hear what people think.

An opinionated blog post on using both Replit and Cursor to build the same app. Which one wins? Would love to hear people's thoughts.

A blog post about sirens. What they are, how they work, and where to go if you want to hear them.

Weather forecasting sites are unnecessarily hard to use. The NWS data is free and easy to access, so I built an app with AI that gives me what I want. If I can do this so easily, what other markets will be disrupted?

I've gathered some data on how the price of single malt Scotch whiskey varies with age (some 50 year olds retail over $30,000). I've dug into the dynamics of the industry to find out why!

Here's what I found out trying out small language models (SLMs) on my local machine: they're good, but you need a powerful machine to run them properly.

It turns out, the Poisson distribution is great for modeling football goals at the league level, but not so much at the club level, despite what's been said on football modeling sites.

Two poems about Ozymandias (king of kings) and some background.

A quick explainer on sonification with several examples and some possible uses cases in business.

Some of my thoughts on the strengths and weakness of code generation and how you can make things better.

Data scientists need to move up the food chain and build their own apps. Even with code gen, that means knowing JavaScript.

I built a chart-heavy data science app using code gen and modern deployment tools. I describe the process and the pitfalls. With the right skills, data scientists can build apps very quickly.

Dalhalla is a concert venue based in an old limestone quarry in Sweden. Its acoustics are supposed to be fantastic. The pictures look stunning. https://www.dalhalla.se/en/om-dalhalla/

I'm working on an app to display charts, analysis, and data on English football league games.

The real goal is to figure out how to use code gen AI (Cursor) effectively for data science projects and to figure out rapid deployment. I'm pushing things a bit harder than you typically see in demo apps (e.g. different chart types (e.g. violin plots, heatmaps, line charts), interactive charts, JavaScript widgets interacting with Bokeh charts, etc).

I'm trying to figure out all the skills, processes, and training you need to build a technical app very quickly. I'm at the deployment stage now.

How urban groundwater could be used with heat pumps to cost-effectively heart homes in Cardiff, Wales. The headline is poor, but the concept is interesting.

How a dinner party 209 years ago gave us both Frankenstein and the modern vampire legend.

An explanation of regression to the mean and some real world examples.

I've analyzed team value and goals scored/conceded in English football. The pattern is clear: more money = more goals scored and fewer conceded. I've made it interactive so you can play with the data.

Creating report using Python and the existing intranet is better than using BI tools to do the same job.

Here's how I built a reasonably complex interactive web app with charts and widgets, that doesn't require a server on the backend to provide data.