Sydney (preference) open to Melbourne | Hybrid (2 days WFO, 3 days WFH) | Permanent Role

Salary: $160k - $170k + super + excellent shares & benefits

About the Role:

Join a fast-growing, D2C scale-up that’s reshaping the consumer wellness experience. With an ambitious roadmap, multiple new product lines in the works, and an international launch on the horizon, they’re expanding their data team and looking for their first Senior/Lead Data Scientist.

This is a unique opportunity to establish the data science function whilst remaining hands-on - setting the vision, standards, and best practices for how data drives decision-making across the business.

While this role focuses on marketing data science, you’ll operate in a uniquely complex environment where physical and digital experiences intersect, combining real-world operations with a seamless online presence.

What We’re Looking For:

A Senior/Lead Data Scientist with experience across both digital and non-digital marketing channels, supporting brand-building efforts as well as marketing effectiveness.

You should be able to confidently explain the rationale behind selecting and deploying different models - whether it’s Difference-in-Differences, Bayesian methods, or Marketing Mix Modeling - demonstrating a clear understanding of each model’s purpose, strengths, trade-offs, and why one approach suits a given marketing challenge better than others. If you can communicate this clearly, you’re exactly who we want.

You’ll be working across key areas including:

• Brand Measurement Frameworks
  
  
• Campaign Effectiveness (both Out-of-Home and Online)
  
  
• Predictive Customer Behavior Modeling (churn, upsell, Customer Lifetime Value)
  
  

What You’ll Need to Succeed

• Experience in consumer or product-led companies with strong brand presence
  
  
• Proven ability to partner with Marketing, Product, Engineering and Customer teams to design and deliver models that measure brand performance, optimise lifecycle marketing, and enhance customer engagement
  
  
• Expertise developing and deploying machine learning and statistical models to transform raw data into actionable predictive insights
  
  
• Deep knowledge of marketing data science, including brand tracking, attribution modeling, customer segmentation, and lifecycle analytics
  
  
• Strong experience in Python and R, with experience using libraries such as scikit-learn, pandas, NumPy, TensorFlow or PyTorch, and tidyverse
  
  
• Comfortable working in an ambiguous, fast-paced environment
  
  
• Familiarity with dbt, and cloud platforms like AWS, GCP, or Azure.
  
  

Interested? Apply now or message Ailbhe on Linkedin if you’re keen to know more!