I'm a data scientist with more than 15 years experience who has worked with major automakers, shipping companies, and F100 companies, I'm looking for my next project. An ideal fit is a small/medium company with green or brownfield problems that need solving.
I'm skilled at building from 0 to 1, I normally do what is now called data engineer, data scientist, and machine learning engineer as one person. My work usually involves finding non-traditional datasources - Once it was USDA data for rural community demographic enrichment, Several times it was getting hands on with people or equipment. If we work together I'll do what I need to in order to solve the problem.
Technologies/techniques: Machine learning/AI, LLM's/RAG, All the tools surrounding ML and AI, A whole host of others.
Contact me if you have a tough challenge I can gnaw on.
I'm a data scientist who has worked with the likes of Porsche and Mulesoft, I'm looking for the next thing.
Some past work:
- In the wild part failure prediction for automotive parts.
- Server fleet failure prediction for Mulesoft. Giving a warning to do load shedding.
- Real-time Vehicle routing, Get a couch from where you are, to where you want it to be.
- Taxi fleet maintenance optimization and failure prediction for a latam taxi company. Saved entire cars.
- Automated sports highlights - Feed in video, get nicely cut highlights of diving catches, touchdowns, etc.
- Wound identification and mangement - Identify what sort of wound, label and categorize the tissue.
- Account grading and revenue optimization for ARM.
- Maritime anti-piracy - Identifying pirate skiffs, at risk vessels, and routing them aroound danger.
Who should contact me: small/medium company with a hair on fire problem that needs solving.
b) A solo founder company with an old tech stack shows practices of many kinds need help in this area. Is Appointment Reminder a dominant force in my chosen market, using current (AI) tech to offer needed features?
If not, I think the story would be encouraging, not discouraging.
The 90s was a time when computers were doubling in speed every 18 months.
I remember office 97* being lightning fast on. A 366mhz celeron - a cheap chip in 1998.
You could build fast software today by simply adopting a reference platform, say. A 10 year old 4core system. then measuring performance there. If it lags then do whatever work needs to be done to speed it up.
Personally I think we should all adopt the raspberry pi zero as a reference platform.
Edit: * office 2000 was fast too with 32 megs of ram. Seriously what have we done?
[Apologies: I mistook the context with my original reply and just realized that]
GP suggested Deloitte and Accenture. They do offer technical consulting services but really as an afterthought specializing in accounting and business consulting. Thoughtworks (home to Martin Fowler, Kent Beck, Zhamak Dehghani and so many more) is far more savvy, had been a far better presence in the industry, and has more highly skilled people. I am a bit partial but with reason.
Oh okay. I thought you had something negative to say about thoughtworks. I’ve known a few people who worked there and thought there was some messy business i didn’t know about.
TL;DR: I recommend it as a workplace and service provider.
In balance, I have absolutely nothing negative to say; I loved working there and felt great about the work we did for others. Consultancies and their clients can be messy but it was a wonderful place to overwork (relative to my personal capacities). The technologists were top notch, people cared to do good work and deliver real business value, and the ambient emotional intelligence was soothingly glorious.
Your semi-regular reminder that Fowler and Beck were part of the brain trust involved with the gigantic disaster that was the "Chrysler Comprehensive Compensation System".
The cognitive radar stuff is old tech. I don’t think that concept is really considered a differentiated capability beyond being a sophisticated implementation.
Almost by definition, any classified computer science research would be non-obvious.
If cr is old tech any keywords for what is new/current tech?
I’m not sure your second point is true. The vast vast majority of classified information is very boring, or operational like frequencies of radar, etc.
Both sides know the basics, it’s what frequencies the radar comms and aircraft work at that is classified.
There’s very little “OMG this one algorithm changes everything!!”. Unless proven otherwise
That is entirely the point, it is supposed to be surprising. There are fragments of circumstantial evidence for some interesting computer science problems e.g. systems that demonstrably imply transitive closure algorithm performance that can’t be remotely replicated by anything in literature.
The ability of someone to imagine the existence of things they are unaware of has no bearing on their existence. You could say the same of a lot of the classified materials science that underpins a lot of US weaponry hardware for which there is ample circumstantial evidence. No one is going to be talking about it on HN.
Location: West coast, remote only.
I'm a data scientist with more than 15 years experience who has worked with major automakers, shipping companies, and F100 companies, I'm looking for my next project. An ideal fit is a small/medium company with green or brownfield problems that need solving.
I'm skilled at building from 0 to 1, I normally do what is now called data engineer, data scientist, and machine learning engineer as one person. My work usually involves finding non-traditional datasources - Once it was USDA data for rural community demographic enrichment, Several times it was getting hands on with people or equipment. If we work together I'll do what I need to in order to solve the problem.
Technologies/techniques: Machine learning/AI, LLM's/RAG, All the tools surrounding ML and AI, A whole host of others.
Contact me if you have a tough challenge I can gnaw on.
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