Data Scientist – Remote

Data Scientist – Remote | EatClub

Join the Food Tech Revolution at EatClub

About UsEatClub is a fast-growing food-tech SaaS company with big global ambitions, co-founded by legendary chef Marco Pierre White and leading industry innovators.

We're on a mission to revolutionise the hospitality industry — helping restaurants boost profitability through smart, data-driven dynamic pricing.

Our platform connects over 2 million customers with thousands of top restaurants, offering real-time deals that can save diners up to 50% off their bill.

With thousands of venues powered by EatClub across Australia and the recent launch in the UK, this is your chance to join a company transforming how people dine out — through the power of data.

Read about us in the AFR:

Read more about us in Broadsheet:

Why You'll Love Working Here

Everyone contributes: Your insights and models will directly shape key product and pricing decisions.

Create big impact: Your work will power smarter pricing, better restaurant performance, and an enhanced diner experience.

Remote-first culture: We're outcomes-focused. Work from anywhere in Australia with full flexibility.

Startup speed, real ownership: You'll experiment fast, iterate quickly, and see your models drive real results.

Inclusive + diverse: We know the best ideas come from diverse minds and experiences.

Work with exceptional talent: Collaborate with world-class product, engineering, and commercial teams solving complex problems in real time.

Supportive, fun-loving team: We work hard, celebrate wins, and always make time for good food.

The Role:

We're looking for a Data Scientist who's passionate about leveraging data to drive smarter business decisions, optimise dynamic pricing, and elevate the way restaurants connect with diners.

You'll work cross-functionally with Product, Engineering, and Growth teams to build predictive models, analyse behavioural data, and uncover actionable insights that fuel EatClub's platform and growth strategy.

What You'll Do:

• Design, build, and maintain predictive models that power real-time pricing and personalised user experiences.
• Analyse large-scale datasets across restaurant performance, customer behaviour, and market trends.
• Partner with Engineering to integrate models into production and monitor performance.
• Build dashboards and visualisations to track key business metrics and model accuracy.
• Design and evaluate A/B tests to validate hypotheses and improve platform performance.
• Translate complex data findings into clear, actionable insights for business and product stakeholders.

What You'll Bring:

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, or PyTorch) and SQL.
• Have worked with AWS (S3, Redshift, Athena, Lambda) or similar cloud data stacks.
• Experience with machine learning, data modelling, and statistical analysis.
• Strong understanding of data pipelines, ETL, and data visualisation (Tableau, Power BI, or similar).
• Solid problem-solving ability and analytical mindset.
• Excellent communication and data storytelling skills — you can turn insights into business impact.

Bonus Points

• If You Have experience in SaaS, hospitality, or food-tech.
• Have worked with AWS (S3, Redshift, Athena, Lambda) or similar cloud data stacks.
• Are comfortable with A/B testing frameworks and experimentation design.
• Love food, restaurants, and dining out — and want to shape the future of the dining experience.

Qualifications

• Degree in Data Science, Computer Science, Statistics, or a related field.
• 3–5 years of hands-on experience as a Data Scientist or Machine Learning Engineer. Full working rights in Australia.
• This is a remote role open to candidates based anywhere in Australia.

Hungry Yet?If you're looking for a role where you can apply data to real-world problems, see your work make an immediate impact, and collaborate with a team that's changing how the world eats — we'd love to hear from you.

Apply now, and help us build something extraordinary — one dataset, one model, one meal at a time.