Principal / Head of Data Science (commercial focus)
Permanent
Can be based anywhere in Australia, but the head office is Sydney
Salary highly competitive $200-280k (depending on experience)
ABOUT THE ROLE
We're working with oe of the most exciting FinTech's in Australia who seeking an Principal Data Scientist to drive measurable commercial outcomes by translating raw data assets into actionable business solutions. This is a hands-on role where you'll build machine learning models, validate them through rigorous testing, and directly influence how they're operationalized and deployed in a live business environment.
You'll work with rich, granular datasets to develop predictive and clustering models that inform pricing, risk assessment, and customer segmentation strategies. Your work directly impacts the bottom line every model you build has a clear ROI attached to it.
KEY RESPONSIBILITIES
* Build machine learning models (from concept through implementation) using supervised and unsupervised learning techniques, with focus on practical business application over theoretical perfection
* Take ownership of 2-3 priority use cases from a larger portfolio; assess them on commercial value and implementation feasibility, then execute against your selected cases
* Work with highly regulated, granular data; identify and mitigate model bias; ensure all solutions meet regulatory and compliance requirements
* Translate complex data science into clear, actionable insights for cross-functional stakeholders
* Collaborate with engineering and business teams to understand how models will be tested, executed, and rolled out; maintain visibility throughout the model lifecycle
* Partner with risk teams to optimize model outputs for business outcomes
* Challenge assumptions; propose new modeling approaches and scenarios that could unlock commercial value
* Deliver analysis and recommendations in simple, compelling narratives that drive stakeholder confidence and action
ESSENTIAL SKILLS & EXPERIENCE
* Deep technical proficiency: ML algorithms (clustering, regression, classification), feature engineering, data cleaning, visualization, and statistical modeling
* Ability to know when to go deep with advanced algorithms vs. when to use simpler frameworks for speed; judgment about effort vs. return
* Experience working with large, complex datasets and ability to augment/engineer new features from raw data
* Understanding of model deployment, testing rigor, and how models get operationalized in production environments
* Regulatory and compliance mindset: experience working within regulated industries; understanding of model bias, fairness, and responsible AI
* Commercial acumen: ability to think about financial outcomes, ROI, and how data science translates to revenue and risk management
* Cross-functional collaboration: comfortable working directly with Product, Engineering, Risk, and Operations teams on a regular basis
* Strong communication skills: ability to explain sophisticated data science concepts to non-technical stakeholders and earn their trust
* Intellectual curiosity: genuinely interested in how models drive business decisions and commercial execution
WHAT WE'RE LOOKING FOR (THE REAL DEAL)
You're someone who:
* Gets excited about the business impact of models, not just the elegance of the algorithm
* Can hold two perspectives simultaneously: the rigorous data scientist AND the commercial operator
* Understands that perfect models shipped late are worse than good models shipped on time
* Has worked in fast-paced, high-ROI environments where data science directly drives revenue
* Can move seamlessly from deep technical work to explaining findings to executives
* Wants to see your models live and working and cares deeply about whether they're a success
* Is obsessive about data quality and model performance
* Thrives in ambiguity and can prioritize your own work based on business value
* Brings intellectual honesty: if a simpler model works, you'll use it; if you don't know something, you'll say so
* Is genuinely curious about how your work gets executed and optimized in production
If this is of interest, please get in touch
#J-18808-Ljbffr