Senior Data Scientist - Pricing & Demand Optimisation

• Shape the pricing of a high-profile consumer product portfolio
• Build advanced models across pricing, demand, valuation and auction optimisation
• Establish a new commercial data-science capability within a transforming organisation

 

The Organisation

Think Talent is partnering with a large, customer-focused organisation undergoing significant commercial and digital transformation.

The organisation manages a distinctive consumer product portfolio where customer demand, scarcity, collectability and market value intersect. It is now investing in more sophisticated data, pricing and portfolio-management capabilities to unlock growth, improve customer outcomes and enable better commercial decision-making.
 

The Opportunity

This newly created role will establish advanced analytical and modelling capability across a specialised consumer asset portfolio.

You will use transactional, behavioural and external market data to improve pricing decisions, understand customer demand and identify the value of premium and collectible assets.

Working across product, category management, finance, digital and technology teams, you will develop models and decision-support tools that influence pricing strategy, auction design, portfolio management and future product development.

If successful, you will: 

• Develop pricing and demand models to understand customer willingness to pay, price elasticity and demand sensitivity.
• Establish analytical frameworks for dynamic and algorithmic pricing across different product segments.
• Build valuation models for individual assets and product combinations, including premium pricing and auction reserve recommendations.
• Apply machine learning and pattern recognition to identify potentially high-value and collectible assets.
• Inform decisions about which assets should be auctioned, released at a premium price, retained or staged for future release.
• Analyse historical transactions, auction performance, customer behaviour, digital journeys and relevant external market signals.
• Test pricing hypotheses through experimentation, simulation and retrospective performance analysis.
• Develop scalable analytical pipelines, visualisations and tools that allow teams to explore pricing scenarios and commercial outcomes.
• Translate complex modelling into clear, commercially relevant recommendations for senior stakeholders and governance forums.
• Create statistically sound, explainable and defensible methodologies appropriate for a highly visible and publicly accountable environment.
• Develop, deploy, monitor and maintain analytical and machine-learning models within a secure production environment, working with technology teams to support reliable implementation and ongoing performance.

 

What You’ll Bring

You are a commercially curious Data Scientist who enjoys solving ambiguous problems and turning complex information into practical decisions. You combine technical depth with the ability to communicate clearly and influence stakeholders who may not share your analytical background.

The must haves include: 

• At least five years’ experience in pricing analytics, demand modelling, valuation or commercially focused data science.
• Experience taking statistical or machine-learning models beyond experimentation and into production, including testing, version control, deployment, monitoring and ongoing model performance.
• Strong knowledge of techniques such as regression, classification, optimisation, clustering and time-series analysis.
• Experience working with large, complex datasets and integrating multiple internal and external data sources.
• The ability to connect analytical insights with revenue, customer, value and portfolio outcomes.
• Strong hands-on capability in Python and SQL, with experience developing models and analytical workflows in Databricks or a comparable cloud-based environment.
• Experience working within cloud-based data and analytics environments, ideally AWS.
• Familiarity with contemporary version-control and CI/CD practices. Experience using Azure DevOps would be advantageous.
• Strong stakeholder engagement and data storytelling skills, including the confidence to influence senior, non-technical audiences.
• A tertiary qualification in data science, statistics, mathematics, econometrics, engineering or another quantitative discipline, or equivalent practical experience.
• Australian citizenship and eligibility to obtain and maintain an Australian Government Baseline security clearance. Candidates do not need to hold an existing clearance.

The nice to haves that will help you hit the ground running include:

• Experience in dynamic pricing, auctions, marketplaces, revenue management, scarcity-driven products or algorithmic decision systems. 
• Exposure to regulated, government-adjacent or highly scrutinised environments would also be valuable.
• Experience gained across digital marketplaces, airlines and travel, retail and ecommerce, financial services, insurance, energy, wagering, luxury goods, collectibles or other environments where demand, pricing and limited supply intersect.

 

Why Join?

This is a rare opportunity to build a new commercial data-science capability around a highly visible and uniquely interesting portfolio.

You will have the scope to shape the analytical approach, introduce new modelling techniques and see your work influence tangible pricing, product and portfolio decisions. You will join an organisation balancing commercial innovation with customer value, transparency and community trust.

Your work will directly shape commercial decisions and help build the foundations for algorithmic pricing, demand optimisation and sophisticated asset valuation.

So, if you are motivated by complex problems, meaningful commercial impact and the opportunity to build something from the ground up, we would welcome your application.