Streamline is a fintech start-up building smart pricing technology that helps businesses make faster, better commercial decisions. We’re looking for a curious and analytical Data Scientist / Econometrician to help turn complex data into practical forecasts, pricing insights, and recommendations. It’s a chance to join an ambitious early-stage company, work on real AI and optimisation problems, and have meaningful ownership from day one.
About Streamline
Streamline is a next-generation pricing intelligence platform developed by Lunio Labs, helping organisations make faster and smarter commercial decisions through machine learning, econometrics, forecasting, and advanced analytics.
We build intelligent systems that turn complex market, behavioural, and commercial data into practical pricing insights, forecasts, and recommendations that can be applied at scale.
This is a unique opportunity to join an early-stage fintech startup with established clients, real market traction, and ambitious growth plans.
We’re looking for highly capable early-career quantitative thinkers who are excited to solve difficult real-world problems using data, machine learning, econometrics, and analytics.
You’ll work closely with experienced technical and commercial leaders while having meaningful ownership over real production models, analytical systems, and product features from an early stage.
If you enjoy learning quickly, solving intellectually challenging problems, and working with smart, motivated people in a fast-moving environment, this role will likely appeal to you.
The Role
We’re looking for a highly analytical and commercially minded Data Scientist / Econometrician to help design, build, evaluate, and improve the intelligence systems that power Streamline.
This role is ideal for someone with a strong quantitative background who enjoys solving real-world problems with data.
You’ll work across areas including:
- Forecasting and econometric modelling
- Pricing intelligence and optimisation
- Machine learning and predictive analytics
- Recommendation and decision systems
- Data analysis and experimentation
You’ll collaborate closely with engineering, product, and leadership teams to help turn complex data into scalable intelligence products.
This is a hands-on technical role with significant opportunity for learning, ownership, autonomy, and growth.
What We’re Looking For
While we absolutely value experience and technical capability, we’re ultimately looking for great people first.
We care deeply about how someone thinks, communicates, collaborates, and approaches problems — not just what’s written on a résumé.
We hire people with:
- Enthusiasm — people who are curious, motivated, and energised by solving hard problems
- Intelligence — strong analytical thinkers who can reason clearly and learn quickly
- Integrity — people who are trustworthy, accountable, and genuinely good to work with
- A sense of humour — because careers are too short not to enjoy the people you work with
Strong interpersonal and communication skills are highly valued. We want people who can collaborate effectively, explain ideas clearly, contribute positively to the team environment, and work well with both technical and non-technical stakeholders.
We are intentionally open-minded on background and years of experience. Whether you’ve recently graduated or already spent a few years working in industry, we’re primarily interested in exceptional people with strong potential and a willingness to learn quickly.
Key ResponsibilitiesPricing & Econometric Modelling
- Develop and improve pricing intelligence, forecasting, and optimisation models
- Build econometric models for elasticity analysis, demand forecasting, and market response analysis
- Assist with evaluating pricing performance and recommendation accuracy
- Analyse behavioural and market data to identify trends, opportunities, and anomalies
Machine Learning & AI
- Develop machine learning models for prediction, optimisation, and recommendation systems
- Help evaluate and improve model performance in real-world applications
- Contribute to experimentation, testing, and validation methodologies
- Work with large datasets and time-series data to improve forecasting accuracy
Product & Platform Collaboration
- Collaborate with engineering teams to help productionise models and analytical pipelines
- Work closely with product teams to shape pricing intelligence features
- Translate analytical findings into practical commercial insights
- Contribute ideas, research, and technical input across the broader platform
Essential Skills & Experience
We are primarily looking for strong quantitative thinkers with deep analytical capability.
Required
- Degree in Mathematics, Statistics, Data Science, Economics, Econometrics, Finance, Physics, Engineering, Computer Science, or another quantitative discipline
- Strong understanding of statistics, econometrics, forecasting, or machine learning fundamentals
- Python proficiency for data analysis and modelling
- Strong problem-solving and quantitative reasoning skills
- Ability to communicate technical ideas clearly
- Curiosity, initiative, and eagerness to learn
Beneficial, But Not Required
- Time-series forecasting
- SQL or modern data platforms
- Cloud platforms such as AWS, GCP, or Azure
- Software engineering experience
- MLOps or model deployment exposure
- Pricing, optimisation, or recommendation systems experience
Why Join Streamline?
- Join an early-stage startup with genuine momentum and growth trajectory
- Work on genuinely interesting AI and optimisation problems
- Flexible remote working within Australia
- Significant ownership and autonomy
- Small, highly capable technical team
- Opportunity to influence both product direction and technical architecture
- Fast-moving environment with the freedom to use modern tools, experiment rapidly, and build without unnecessary bureaucracy
- Real-world commercial impact from the work you build
Apply
If this sounds interesting, even if you don’t perfectly match every requirement, we’d still encourage you to apply.
We’re much more interested in exceptional people than perfectly optimised CVs.
We encourage the use of AI to assist with your application, but please make sure you tell us your story, why you want to join a company like Lunio, and what differentiates you from other applicants.
Education:
- High School (Year 12) (Required)
Language:
Work Authorisation:
Location:
Work Location: Hybrid remote in Australia
