Data Scientist

About the Company

Streamline is a pricing intelligence platform from Lunio Labs that helps businesses make quicker, better commercial decisions using machine learning, econometrics, forecasting, and advanced analytics.

The platform is designed to transform complicated market, customer behaviour, and commercial data into usable pricing recommendations, forecasts, and insights that can be deployed at scale.

This opportunity is with an early-stage startup that already has established customers, proven traction in the market, and ambitious plans to grow.

The team is seeking early-career quantitative problem solvers who are excited by challenging real-world problems and enjoy working with data, machine learning, econometrics, and analytics.

You will partner closely with experienced technical and commercial leaders, while taking on real ownership of production models, analytical systems, and product features from the beginning.

If you learn quickly, enjoy intellectually demanding work, and like being around smart, driven people in a fast-paced environment, this role should be a strong fit.

The Role

Streamline is hiring a highly analytical Data Scientist / Econometrician with strong commercial thinking to help design, develop, test, and enhance the intelligence systems behind the product.

This position suits someone with a solid quantitative background who likes applying data to practical, real-world challenges.

You will work across forecasting, econometric modelling, pricing optimisation, machine learning, recommendation systems, and data-driven experimentation.

Day to day, you will collaborate with engineering, product, and leadership teams to convert complex datasets into scalable intelligence products.

This is a hands-on technical role with strong scope for learning, ownership, autonomy, and career growth.

What the Team Values

The company values how people think, communicate, collaborate, and solve problems, not just what appears on a résumé.

The team looks for people who are curious, motivated, and energised by hard problems; sharp analytical thinkers who learn quickly; trustworthy and accountable team players; and people with a sense of humour.

Strong communication and interpersonal skills are important, as the role involves working effectively with both technical and non-technical stakeholders, explaining ideas clearly, and contributing positively to the team.

The company is open on background and years of experience, and welcomes both recent graduates and candidates with a few years of industry experience, as long as they show strong potential and a willingness to learn fast.

Key Responsibilities

• Improve and develop models for pricing intelligence, forecasting, and optimisation.
• Create econometric models for elasticity, demand forecasting, and analysis of market response.
• Support measurement of pricing performance and the accuracy of recommendations.
• Examine behavioural and market data to uncover patterns, opportunities, and unusual movements.
• Build machine learning models for prediction, optimisation, and recommendation use cases.
• Assess and refine model performance in real-world settings.
• Contribute to testing, experimentation, and validation approaches.
• Work with large and time-series datasets to strengthen forecasting accuracy.
• Partner with engineering teams to help move models and analytical pipelines into production.
• Work with product teams to shape features for pricing intelligence.
• Turn analytical findings into actionable commercial insights.
• Share research, technical ideas, and product input across the platform.

Essential Skills and Experience

The role is aimed at strong quantitative thinkers with excellent analytical ability.

Applicants should have a degree in Mathematics, Statistics, Data Science, Economics, Econometrics, Finance, Physics, Engineering, Computer Science, or another quantitative field.

A solid grasp of statistics, econometrics, forecasting, or machine learning fundamentals is required, along with Python skills for analysis and modelling.

The role also calls for strong problem-solving ability, sound quantitative reasoning, clear technical communication, curiosity, initiative, and a willingness to learn.

Useful but not mandatory experience includes time-series forecasting, SQL or modern data platforms, cloud environments such as AWS, GCP, or Azure, software engineering, MLOps or deployment exposure, and experience with pricing, optimisation, or recommendation systems.

Why Join

Join a startup that is already gaining traction and building toward further growth.

Work on interesting AI and optimisation challenges with real commercial impact.

Enjoy flexible remote work anywhere within Australia.

Take on meaningful ownership and autonomy in a small, highly capable technical team.

Help shape both product direction and technical architecture.

Operate in a fast-moving setting with room to use modern tools, test ideas quickly, and build without unnecessary bureaucracy.

Your work will directly influence outcomes for real customers and businesses.

Application Notes

Candidates are encouraged to apply even if they do not meet every single requirement.

The company is more interested in exceptional people than a perfectly polished CV.

AI may be used to support the application, but the submission should still explain the candidate’s background, why they want to join a company like Lunio, and what makes them stand out.