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Grosvenor

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sshack@gmail.com

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My hypothesis is markets are fractally efficient and fractally competitive. Much like a strange attractor, they swing between states of efficiency and competitiveness.

The default regime is instability. Computational capacity is unstable through time, and the problem size itself changes (fractally) through time.

SEEKING WORK | Data scientist consultant | Canada/Remote Worldwide

Most of what people call "data science" is now doable with an LLM and a weekend. I focus on the messy, ambiguous, regulation-heavy gnarly problems where nobody is sure what the right question is. Often it involves getting hands on to find the data and signal that's really needed.

What I've done:

   - AI verification of building and architectural BIM/CAD against 400 page ESG standards. (Days of work down to minutes)
   - Part failure prediciton, saving a German automaker from lemon law recalls. ($20M+ exposure avoided)
   - Oil & gas well and lease production forecasting. 
   - Real-time emissions detection for industrial smokestacks. ($75K fines per incident prevented)
   - Revenue optimization and persona identification for debt collections (15-20% net revenue lift)
   - LLM-based legal document extraction (land runsheet), reducing due diligence turnaround from 3 days to 30 minutes
   - Built vessel piracy risk engine that informed naval escort deployment, contributing to fewer hijackings
Things I'm unwilling to work on:
   - Gambling.
   - Ads/Surveillance.
   - Payday loans/rent-to-own.
Email me with a short description of your problem. If it's hard enough, I'll reply within 24 hours.

A major plot point in the Red Dwarf books is about Coca-Cola sending a fleet of space ships out to blow up stars so they can spell "Enjoy Coca-Cola" in the sky.

One of those ships crashes and the boys from the Dwarf find the service mechanoid, which is how they get Kryten.

How could I forget this! He also recommended the name.

Wolfram had come up with some normal techie names "computron", "math-o-matic" or whatever. SJ said No those suck, use something simple like Mathematica.

Steve Jobs and Stephen Wolfram were friends for years. Mathematica shipped preinstalled on early NeXT systems.

SJ recommended some of the UI bits of the notebook. Particularly the separators between cells.

I'm using AI to de-compile NeXTStep applications back to Objective-C source code.

The idea is decompile something like Wordperfect or Framemaker, then port the NeXTStep code to GNUStep and have WP on GNUStep/Linux.

I've gotten the north Korean wanting to use my upwork account... I'd have to create one first.

But now the Nigerian "format" scammers are into job scams. I got an email that reeked and played along a bit. I was "hired" after a curiously simple interview via signal, and had to wait for my "supervisor" to come train me.

Eventually I got the "boss" on the line to talk, he went absolutely postal when I asked if he was an African scammer. Apparently that's racist now.

SEEKING WORK | Data scientist consultant | Canada/Remote Worldwide

Most of what people call "data science" is now doable with an LLM and a weekend. I focus on the messy, ambiguous, regulation-heavy gnarly problems where nobody is sure what the right question is. With AI as an execution lever, of course.

What I've done:

   - Saved a German automaker from lemon law recalls. ($20M+ exposure avoided)
   - Real-time emissions detection for industrial smokestacks. ($75K fines per incident prevented)
   - Revenue optimization and persona identification for debt collections (15-20% net revenue lift)
   - LLM-based legal document extraction, reducing due diligence turnaround from 3 days to 30 minutes
   - Built vessel piracy risk engine that informed naval escort deployment, contributing to fewer hijackings
Things I'm unwilling to work on:
   - Gambling.
   - Ads/Surveillance.
   - Payday loans/rent-to-own.
Email me with a one-paragraph description of your problem. If it's weird enough, I'll reply within 24 hours.

Back when I was a young lad I wanted engineering to be a real discipline - formal qualifications, codes, held to account, and limitations on who could call themself an Engineer(TM).

But the money was so good we (The royal we) didn't think we needed it, that would just get in the way. Did you see how much FB employees were getting paid in 2015! Insanity! Now, even the skutters have a better union than us.

A plumber, or an electrician has a better union, and hence rights and protection than us.

But if you're building a brand new field you can still build a guild.

No one. The influencers are simply telling you you're wrong if you think you need that.

Which is the thing, we do need a single key that can be used for all those things. So we get PGP.

I don't enjoy writing authN code, or frontend code, or all the myriad bits of glue converting between one thing and another.

Now, I'm master of about a thousand lines of pricing code plus documentation and research which actually matters. The AI can handle the rest as a very skilled junior with a TBI.

You absolutely are a proctor, or senior manager. The AI is the smartest most well read junior you will ever meet, but don't go out of its happy path.

As you go out of the commonly read happy path for CRUD apps, you'll have to get more and more involved. I wouldn't write a new kernel design with AI right now, I might write a Linux kernel driver with it though.

I would expect that within a couple years, these other disciplines can be baked in enough the machine costs less for everything but surprises.

They already are. I’m successfully using frameworks like bmad to deliver complex apps at that level. My job is to manager the see, as, ux, sre processes and catch errors.

I spend more time refinding prd , epics and stories than I do elbows deep in code.

If I don’t like the output of a story I nuke it change the story and have the flanker try again. I’m using the open source glm, kimi, deepseek models. I expect the full pipeline to be good enough by the end of the year.

SEEKING WORK | Data Scientist / Consultant | Canada/Remote Worldwide

I'm a data scientist with over 20 years of experience specializing in solving hair on fire problems. I thrive on gnarly problems AI can't complete even if walked through the problem step-by-step. Often it involves getting hands on or talking with staff to find the data that's really needed.

My past work includes:

   - Saving a German automaker from lemon law recalls.
   - Helping a major cloud vendor predict server failures to enable load shedding.
   - Real-time on demand routing logistics work .
   - Airline flight delay forecasting.
   - Oil & Gas forecasting.
   - Shipping piracy risk.
   - Wound identification and classification.
   - Revenue optimization, persona identification and dynamic "risk-on/risk-off" risk management for ARM.
I'm currently working on spec work with criminology typologies of victim disposal in serious crime. The tigger for this is the Justo Smoker murder of Linda Stoltzfoos, Police spent months searching in the wrong places, when a good behavioural model would have shortened the search time signifcantly. I'm unlikely to get it in the hands of law enforcement, but I like solving a good problem.

Things I'm unwilling to work on:

   - Gambling.
   - Ads/Surveillance.
   - Payday loans/rent-to-own.
Get in touch if you have a really difficult problem you're trying to solve. Email in profile.