Data scientists in the driver’s seat
Last week about 60 rally teams, close to 500 volunteers and a small organising group staged the Targa Rally of New Zealand.
This year’s Targa was the 25th running of the iconic event – billed as the ultimate road race – which involves close to 1200km of public road closed and turned into racetrack.
Last May my Targa team were doing great until stage three of the second day when some Gentle Annie shingle shredded the Kevlar cambelt on our Type R, rapidly followed by 16 valves and four pistons. Not an easy fix.
So this year we were back with a new top end and a new state of tune. And the good news is that it worked. We ended up 1st in class and 6th overall in the regional rally, managing to beat cars with engines more than twice our capacity.
The secret was the new state of tune that Adam the mechanic had been able to finesse out of the little Honda, coaxing 231 horses out of a diminutive 1.6 litre straight four engine.
In an age where a car’s Engine Control Module (ECM) is the engine’s brain, the arms race for power pivots around the dynotuners who programme the ECM. A good dyno-tuner can charge big bucks for a race tune and that price is only going north.
The same thing is happening in business right now when it comes to data scientists.
Last year the London School of Economics described data science as the weapon of choice in the global arms race for artificial intelligence.
In my opinion AI (and more specifically the subset of AI known as machine learning) is the single largest technology trend affecting the future of business.
Two years ago Google CEO Sundar Pichai moved Google to having an AI-first strategy, because he saw it as the keystone to the company’s future.
Likewise last year Amazon CEO Jeff Bezos acknowledged that machine learning was the enabler that would let Amazon remain the largest retailer in North America. A statement that wasn’t lost on Alibaba founder Jack Ma, who’s in the process of buying up American AI patents as fast as he can.
But it’s not just retail and it’s not just the web giants. A report out last week from the AI Forum of New Zealand looked at current use of AI in Aotearoa and the potential to double it through smarter and more targeted use of data.
It’s far from a theoretical discussion. Farmers have been quick to apply AI to applications as diverse as remote livestock sensors, drone-based herbicide delivery and monitor animal health.
A mate of mine in the Wairarapa uses a combination of sensor collars, GPS and a cellphone to monitor the health and whereabouts of 250 angus cows.
Three months ago I saw another impressive demonstration of agricultural AI by Dunedin-based Iris Data Science.
This business has used AI to deliver face recognition of sheep. Effectively a tool that does away with old-school ear tags and replaces them with a sensor that can recognise each sheep as it enters a pen. The video-based software can display the animal’s entire life history to the farmer in real time. A history that’s able to follow the animal as it’s processed and/or exported.
Meanwhile, in the Hawke’s Bay, T+G Global (previously Turners and Growers) is harvesting apples with an AI-driven robotic apple picker. The harvesters move independently between rows of trees and use machine vision to work out which apples are ripe, then suck them off branches via a vacuum.
The AI-driven software prevents underripe apples being picked and is not affected by the vagaries of the labour market, immigration and health and safety requirements.
To create and configure all these applications, you need someone who can turn massive amounts of data into information, information into insights, insights into action, and drive that action with intelligence. This is what a data scientist does.
The role of data scientist has been called one of the sexiest jobs of the 21st century, and as big data has moved mainstream it’s this group of workers who will unlock AI-driven growth in companies.
And that capacity doesn’t come cheap. While www.payscale.co.nz lists the average data scientist starting salary as $78,000, the last two companies I know who have employed them have paid well over $150,000 and that number is only going up.
The New York Times reports that data scientists in Silicon Valley are now pulling down more than US$250,000 (NZ$393,000) per annum plus shares.
Here in New Zealand it’s mainly been the big local players who have been hiring them – companies like Trade Me, Xero and Weta Digital.
But that’s about to change as the local businesses wake up and smells the data-laced coffee. Then it’s going to be a land grab.
When I challenged my engine rebuilder about the affordability of spending $2000 for a few hours of dyno tune for the Honda, he laughed and said I couldn’t afford not to.
Going forward, the same’s going to be true of businesses employing data scientists.