For as long as he can remember, Jonathan Toner has been drawn to the hardest problems he can find. Where did life originate? What can Earth’s most extreme environments tell us about the planet’s history? Was Mars always the desolate, lifeless place we imagined it to be?
Toner investigated these and other questions as a research assistant in earth and space sciences at the University of Washington (UW), where he also earned a Ph.D. in geophysics. After more than a decade in academia, he joined the Amazon Flex team as a researcher in 2020. It was an eyebrow-raising move: The two careers have very little overlap in subject matter. But crucially, both require an explorer’s mindset.
From a young age, Toner was different from his peers. Like other kids, he went to the library to find fun, entertaining reads, but young Jonathan also checked out books on relativity, number theory, and calculus.
“I was quite curious – maybe a bit strange,” he says. “Subjects that other people tend to avoid as too difficult, I will see as a challenge.” When it came to choosing a major at the College of New Jersey, the choice was easy: “I had heard that physics was the hardest, so I did.”
Make the transition to tech
When high school beckoned, he decided to combine his passions for science and the outdoors by studying at the UW, which is close to the Cascade Range. A few months later, much to his delight, he conducted field studies at the McMurdo Dry Valleys in Antarctica. It was the first of three expeditions to Antarctica, with the latest in 2017, funded by NASA and the US National Science Foundation.
I would write an application and say: ‘I have a Ph.D. in geophysics and I studied planetary science. They would look at it and say, ‘Who is you?’
Antarctica is a fertile area for scientific study – particularly the effects of climate change, but also as an analogue to the extreme environments found on Mars or the icy moons of Jupiter or Saturn. In his pursuit of increasingly difficult questions, Toner moved from physics to geophysics to planetary chemistry to astrobiology. He even investigated the watery origins of life itself.
In 2019, Toner was at the top of his game: a strong publication record and research funding for his ongoing projects at one of the world’s leading institutions for planetary science. But looking into the distant future, he didn’t like what he saw. He had a strong desire to remain in the Seattle area, but he felt his opportunities to advance in academia were limited and he had a young family to support, so Toner decided to look for opportunities in the technology industry.
“I had friends in tech who were doing really well and could live wherever they wanted,” he said. “And I thought to myself, ‘I can do that’.”
He began applying for a few positions, but his situation was unusual, to say the least: “I would write an application and say, ‘I have a PhD in geophysics, and I studied planetary science. They’d look at it and say, ‘Who is you?'”
This is where Toner’s intellectual tenacity started. He had very little need for machine learning in his field and limited programming experience. So, utilizing his strong academic fundamentals, he taught himself both.
“I bought a bunch of textbooks on machine learning and statistics. I read them. I did the problems. I took about 10 online courses,” he says. “I taught myself how to build machine learning models and the Python programming language.” And he did all that in just three months.
And while Toner didn’t have specific experience in the tech industry, he had credentials in other technical fields. In particular, he had developed complex applied models, including thermal and physical diffusion in Martian soil, and thermodynamic models of multicomponent solutions.
“Machine learning might be a step down in complexity from that,” says Toner, “but it’s like trying to measure the difference in difficulty between playing the violin and the piano.”
That approach worked, and in May 2020 Toner joined Amazon in the logistics space.
Satisfying Two Kinds of Customers on Amazon Flex
Package delivery to Amazon customers is done in a variety of ways, including via Amazon Flex. Launched in September 2015, Amazon Flex offers individuals the flexibility to use their own vehicles and set their own schedules while making deliveries as a way to earn extra money. Amazon Flex drivers pick up customer orders from a local Amazon pickup location and deliver them directly to customers. The Amazon Flex business was built to support Amazon’s growth and meet customer expectations for fast deliveries.
Amazon Flex drivers are also our customers. So we have this dynamic of multiple customers to satisfy, and it becomes a really complex scientific problem. How are you holding up all happy? It’s a fun problem to think about.
Toner’s overall goal is to find cost-effective ways to keep Amazon Flex drivers happy and sign up for more blocks, ensuring the service has enough driver capacity to meet expected demand.
“Amazon is customer-obsessed, and you usually look at the customer as the person receiving a delivery. But Amazon Flex drivers are also our customers,” says Toner. “So we have this dynamic of multiple customers to satisfy, and it becomes a really complex scientific problem. How do you keep all happy? It’s a fun problem to think about. It takes up all my time.”
As independent contractors, Amazon Flex drivers have the flexibility to accept bids and schedule roadblocks at their convenience. That means Amazon needs to make sure the program is attractive to drivers so they feel confident their time is well spent with Amazon Flex. This can be through a combination of things, such as block pricing, promotional activities and desirable delivery windows.
“A lot of our work is about predicting what Amazon Flex drivers will do, what they want, and making sure they have a good experience,” explains Toner.
Amazon Flex has been active in the US since 2017 – and it’s growing fast.
“Given the number of Flex depots and working drivers in any given week is so large, manual adjustments are impractical,” says Toner. So he works with Amazon’s product and business operations teams to create smart, autonomous systems that balance customer needs.
Since joining Amazon Flex, Toner has been promoted to senior researcher and has created an entire ecosystem of machine learning models and optimization tools. This ecosystem is orchestrated to recommend recruitment drives for Amazon Flex in the US. It takes into account expected delivery demand, predicts capacity contributions from existing drivers and potential new recruits, and predicts how drivers will flow through the onboarding process.
“What fascinates me about this ecosystem of tools is that it’s a lot of different models that all interact with each other,” says Toner. “And it has allowed me to work on so many approaches: Markov chain models driven by logistic regression, recurrent neural networks, dynamic programming to find optimal policies. It certainly keeps me interested.”
Intellectual freedom
Toner also appreciates the leeway he gets to create this smorgasbord of tools.
“Coming from academia, I had some reservations. I was worried about being micromanaged. But I was very pleasantly surprised,” says Toner. “My colleagues are lovely people – so smart and supportive. And, most importantly, they give me the freedom to do my thing.”
There is rich science to do with a company like Amazon that is not available anywhere else. I have grown tremendously as a scientist because of it.
Right now, Toner’s thing is the ongoing expansion of his suite of models, which so far is focused on the US.
“I want to expand worldwide and I’ve had interest from Amazon Flex in different countries,” he says.
He also works on long-term planning for Amazon Flex, which means modeling driver capacity years in advance. “This is a very difficult question. I mean, where do you even start? To me, it’s a gold mine.”
Does Toner have any advice for others in academia considering entering the tech industry?
“When you’re in academia, it’s really like an ivory tower, and going to business can be viewed with pessimism,” he says. “But I would strongly argue against that. There’s rich science to be done with a company like Amazon that isn’t available anywhere else. I’ve grown tremendously as a scientist because of it.”
Toner also advises against limiting yourself based on what you think you can do:
“Science is really about the interesting questions, isn’t it? So focus on the questions. The methods will come.”