Tractor Ventures Full Stack Engineer Lauren Jarrett takes the time to share her perspective on all things engineering and AI as Tractor scales in a technical capacity to continue funding many more founders into the future.
The career path to Tractor
Gaz: Hi Lauren, welcome to the Tractor hot seat. Before we get into your technical work with Tractor, I'd love to know a bit about your career background.
Lauren Jarrett:
So, I graduated with an economics and finance degree and went to work in Defence. I initially started with economic consulting in Canberra. I then moved to Brisbane when the oil and gas capital projects were getting quite big and began a role in supply chain analytics.
From there, I progressed to business performance and reporting, as I had always been quite numerically minded in the finance-focused maths side of things. I just liked the way that you would use data for storytelling and to gain visibility over what was going on.
As part of the role, those aspects of Excel programming were fun, and I really enjoyed that.
Gaz: So, I'm presuming the roles got progressively more technical from then on?
Lauren Jarrett:
Absolutely - I actually followed a boss who moved roles and began in my first analytics roles proper with Goodstart Early Learning. There, I started to work on business intelligence solutions that were really comprehensively built out, where I could build out suites of reporting to help operations run really well.
We had a centre director plus 640 centres that could log in and see their individual dashboards, and the different levels of management could all login and see their own bespoke dashboards, which was pretty amazing.
From there, I ended up at CBA, where my role progressed even further into the technical aspects of data, data storytelling and querying. That's where I started to get exposed to the Data Science spectrum.
Up to that point at Goodstart, I'd been working with a statistician to tell stories with data and make sure they were relevant and the correct stories, and it was fun to get exposed to that.
But then, the person I worked alongside at CBA had a PhD in machine learning. At that stage, we were working with trends in many of the data sets that the bank owned for transaction banking clients and were focused on making relationships sticky between customer and bank.
After that, I moved to San Francisco and then got stuck in Toronto during COVID while working remotely as a data analyst. I started to get more into the backend side of engineering, but I also told stories with their data and built that out.
I soon returned to Brisbane and got my first role as a software engineer with a venture studio, Josephmark, before I came back to finance with Tractor!
Doing the good work
Gaz: That's an amazing career arc. So, let's talk about where you think your best work gets done in Tractor.
Lauren Jarrett:
I guess our best work gets done in a long-term planning focus. Because I work as a software engineer, I feel like a lot of my work is focused on looking at and understanding the trends in the data and then extrapolating that to understand and uncover better ways to service customers.
But that can also be quite a long-term focus because we're looking at this not just in the next two weeks or the next three years but even longer term. How can we get value from our data to help our customers access a better cost of funds, and how can we better meet their problems? What products could be better designed for them?
And then, because we're also a startup, much emphasis is put on the system side of things, working with instant customer feedback and across various tasks and tickets that have excellent outcomes for our team.
Tractor: funding founders, and...
Gaz: How about the external perception that Tractor just loans money out, as opposed to the reality of what the engineering team are building to scale in a really technical fashion?
Lauren Jarrett:
I guess giving money out (as Tractor) has a simplistic lens. Our role and what our team does is quite a market-leading credit and loan application system, where we take a lot of inputs and then automatically try to garner as much information as possible so that the evolving loan application process can be easier and simpler, with lower need for repetition.
We sit in a really interesting space working with businesses and startups, which is automatically quite difficult to do. If it was easy to know what startup to fund, then investors would be very happy with that and that's realistically what we're trying to do.
So, our role really involves supporting the entire team and helping them assess what would be a good business to help fund, what is the right amount of funding and when is the right time for funding.
We use AI to help automate things under the hood and gather insights from lots of data to try and make it as simple and seamless as possible for the end user. Ideally, they won't know that when they land with us because it operates in the background giving the user a quick, easy and painless experience.
The (technical ) future of Tractor
Gaz: So what does the future look like for customer experience at Tractor from a technical perspective?
Lauren Jarrett:
Getting faster.
As we started to build our own models, the more data that we have the better. But as time goes on with patterns and trends, over time, things will get simpler, faster and easier for the customer.
They should be able to spend less time on completing the application. The AI space is evolving so rapidly at the moment and is going to continue to evolve, which is pretty exciting to be able to explore and test the emerging technology.
We'll be able to do that as well because we already work with it, have it embedded in our systems and have the right mixture of people and skills to critically assess what technology we should look to pursue, build custom or leave until it's more mature. We're at the forefront of taking advantage of that.
Solving Puzzles
Gaz: What feels good to you in a working environment?
Lauren Jarrett:
I really love challenges. I love puzzles, overcoming problems, and asking, 'Why does it need to be done this way?' That's always a good question.
And then, as a team culture, I enjoy working with startups because their approach aligns with how I see the world. 'Why does this have to take so long? Why does it have to do this?'
We have a really great team here. A team with a really good balance of skill sets, especially in our example of an engineering team, which is just three of us. Quite a small team to get done what we get done, and we get to build an awful lot.
We do that by having the right culture and a really good product person who helps us focus on building the right things at the right time.
Large Complex Environments
Gaz: How about your past work in a large complex banking environment, as opposed to this much leaner operation?
Lauren Jarrett:
Big banks are great, but when you are a person who likes to get things done, you can become very disconnected from working with the end customers in a big bank on a day-in and day-out basis. Because you only sometimes see the changes in the system, you don't always get feedback from the customer.
I think big banks, having primarily worked on the institutional side of things, which is the big, big business lending, see and understand scale from a different perspective, which I think is always really important to consider.
But I guess I really like the scrappy mentality of 'we don't have the funds' or, 'we're out of time.'
'Can we just quickly get onto this and kind of hack our way through the solution by working around the obstacles?'
In big organisations, there are many people, and so, by default, things just naturally need to move a lot slower by having to consult more stakeholders. I really like the speed of working at a smaller company, which can be scrappy. We have an excellent advantage in that space.
Because we are small, we can experiment a lot more, have a chance to be creative with ways of solving the customer's problem. I love a test-and-learn mentality, and with where things are at the moment, I think our customers really like that because we can respond to their needs a lot faster than others can.
Sourcing inspiration
Gaz: Brilliant. How about sourcing inspiration in how you work? External or otherwise…
Lauren Jarrett:
Absolutely. Because our team uses Go (programming language), I was very new to it when I joined. So, reading about what we've done and all the resources that Matty (Evans, Director of Engineering) has created as our standards is inspiring.
We're thinking about how to do this at scale by focussing on structuring a codebase, and anticipate more people on board eventually.
I look at what other companies are doing in the space and read about what finance companies are doing, such as data usage at hedge funds, for example.
I always get inspired by just thinking about the creative ways people use data to solve problems. AI is evolving so rapidly, which I find really interesting. It's easy to be inspired in that space at the moment because technology is moving fast and new things are emerging all the time.
The appeal of the Tractor mission
Gaz: Finally: a fun fact on how you found your way to Tractor?
Lauren Jarrett:
It was probably just serendipity. I was browsing around and thought, 'Oh, I do want to return to finance.'
Then I saw Tractor and read the story about 'Why Tractors?' And I really loved that analogy—I thought it was such a great way of explaining the problem the team was trying to solve.
Having come from a venture studio where everyone talks about rockets all the time and shooting for the moon. I liked that analogy because there's a different need for it. VC is great; it has its own place.
But for a lot of businesses, it's more important to grow slowly and more sustainably. As a finance person, I really like and value Warren Buffett's approach, in which he's always said, 'I'm the only person in the world who tries to get rich slowly.'
That's an important mindset to have when you are trying to build a business - and personally, in the long term, sustainability is important rather than trying to grow at all costs for short term gain.
Elastic capital and what it means...
Gaz: Last one now. Elastic capital means, to you…
Lauren Jarrett:
Tractor is best placed to work in the market. It has a really good niche and understanding because it works closely with founders to understand their businesses and then lends money to them for their specific needs.
When I think about 'elastic capital' I think if something that iterates over time, ie you get a loan, you top-up, you have initial capital funds for *this*, you come back and top up for *that*.
Sitting on the debt side is a really important space to be in because you're not taking away ownership equity. You can work closely with the founders to help them solve their problems and provide them with the proper funding to implement their solutions.
I feel like Tractor is very good at understanding its role in the market and how we can continue to serve our customers best. The difference between needing equity and when you would use debt is truly important, as we're ensuring we're solving the right problem for founders. We do have that relationship with a lot of our founders.
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