Data Scientist

Lorikeet is the most powerful customer support AI for complex businesses like fintechs, healthtechs, marketplaces and delivery services.

We’re doing this by building ground up from the premise that most support responses should be automated with transparent, customizable AI, and that support teams should spend their time managing automation and engaging with complex cases, not grinding through high volumes of simple tickets. Once teams are freed from reactive support, we want to help them tackle what’s next: providing personalized concierge services to their customers.

To deliver this combination of powerful AI systems and well designed tooling we’re leveraging Jamie’s experience as an early member of Google’s generative AI team and Steve’s experience building for operational teams at Stripe, as well as the experience of our team who’ve joined us from places like Stripe, Canva, Atlassian, Dropbox and Dovetail.

We are growing fast, have paying customers, real revenue, an exciting roadmap and a strong sales pipeline. We’re well funded by leading VCs and angel investors, including Blackbird, Square Peg, Claire Hughes Johnson (ex Stripe COO), Cristina Cordova (Linear COO), Bob Van Winden (Stripe Head of Support), and Cos Nicolaescu (Brex CTO).

Our global customers include:

• The largest telehealth company in Australia,

• The largest bank for teens in the US,

• One of the largest NFT marketplaces by trading volume,

• The leading virtual specialty-care platform in the US,

• One of the largest flexible rent-payment platforms in the US,

• One of the largest Web3 gaming companies

… and a handful of other enterprise customers with over 1 million support tickets a year.

• Warm, mature, in-office flexible culture. Low ego, high trust team. No tolerance for ‘talented jerks’. We value working together in-office as the default in our (quite nice!) Surry Hills office. We embrace a) working efficiently, and b) working flexible hours to fit in life priorities outside of work. We’re committed to building a diverse team and really encourage folks from underrepresented backgrounds to reach out - we value user obsession and eagerness to learn over traditional credentials.

• High pay, high expectations, high performance. We aim to match unicorn / scale up pay at base salary and offer a potentially life-changing equity stake in the business. Our team gets the same monthly updates we send to our investors because they’re investors and owners too.

• On the technical cutting edge. With our users we’re defining what an AI-first SaaS product looks like. No one has figured out what the UI/UX, capabilities and data models of an AI first company are - it’s white space for us to invent. The AI agent problems we’re solving are beyond the cutting edge at the biggest research labs. We’re building on a modern tech stack, with Typescript, React/Remix, PrismaORM, NestJS and some Python sprinkled in.

• No nonsense recruitment process. The process is: 1) informal chats with Amy and Remy to hear our pitch and understand your interests and goals, 2) a ~two day paid work trial where you come in and ship with us. There’s no better way for each of us to figure out if we like working together than to work together!

Lorikeet is looking to bring on its first data hire to join the team in Sydney. Our Data Scientist will build the foundations for how we use data to run and grow the business. You’ll work across teams to help us make sense of what’s working, where we’re flying blind, and where we should make meaningful changes. This is a rare chance to build a data function from the ground up and make a major impact on one of Australia’s fast-growing AI companies.

Over time, you’ll help define what “data-driven” actually looks like at Lorikeet—not just reporting on what’s happened, but surfacing insights that unlock new possibilities for how we serve our global customers and win new ones.

What you’ll do

• Audit and refactor our data systems to make them reliable, accessible, and future-proof

• Build and maintain internal dashboards that track customer health, account performance, and core business KPIs

• Define source-of-truth metrics and hold GTM, product, and engineering accountable to maintenance of data integrity

• Run ad-hoc and recurring analyses to support account management, strategic decisions, and product prioritization

• Help the team understand not just what’s happening, but why

• Spot gaps, eliminate manual work, and proactively improve the way we use data across the company
  

The right candidate

We're looking for a senior-level data scientist to help us turn a breadth of data into meaningful insights. We need someone who is comfortable working independently and making calls without perfect information. This role is ideal for someone who has experience collaborating with engineering, go-to-market, and leadership in stitching pieces of a business together to tell a story.

We need clean foundations, sharp dashboards, and real-time signals on what’s working and what isn’t. If you’ve worked at fast-moving startups before, you’ll know exactly what this looks like.

You might be a fit if you:

• Have 5-8+ years of experience in data science, analytics, or BI—especially in early- or growth-stage companies

• You’ve successfully and independently designed and owned a modern data stack (dbt, SQL, Airflow, Metabase, etc.)

• Have demonstrated experience balancing statistical rigor with quick delivery of useful insights

• You’ve led cross-functional work streams involving product, engineering, sales, or customer success—and have the receipts to show you made things measurably better

• Have strong instincts for what metrics matter in B2B SaaS and customer-facing work

• Are excited by the chance to help build a category-defining AI company
  

If you don't quite match this and are from an under-represented background we strongly encourage you to reach out. We know first hand that diverse teams are higher performing and are proud that our team reflects a broad spectrum of identities and lived experiences.