Salary: $190k–$200k base + super
Sector: Financial Services

The Opportunity This is a brand-new, high-impact role within a major financial services organisation where data science is measured by one thing: commercial impact. The focus is on building production-grade customer and retention models that directly influence revenue, growth, and portfolio performance.

This is not reporting or support analytics. It’s end-to-end ML ownership. You’ll design, build, deploy, monitor, and evolve models that drive customer retention, engagement, and lifetime value, with real influence across marketing, pricing, credit, collections, and customer strategy.

The role is heavily hands-on and technical. Most of your time will be spent on model development, data wrangling, feature engineering, hyperparameter optimisation, deployment, and monitoring, with some exposure to data engineering and MLOps.

What You’ll Be Doing

• Build customer and retention models end-to-end
• Lead ML solution design from business problem to production
• Develop models in Python for batch and real-time deployment into Azure
• Own the full model lifecycle: build, deploy, monitor, retrain
• Partner with business and product teams to embed models into decisioning
• Deliver models that directly impact revenue and P+L

Tech Environment

• Data: Snowflake
• Modelling: Python
• Deployment: Azure ML Studio / Snowflake
• Monitoring: Streamlit
• Version Control: Azure DevOps
• GenAI: Azure AI Foundry

What They’re Looking For

• Strong experience building production ML models
• Background in customer analytics, retention, or marketing modelling
• Excellent Python and ML engineering capability
• Experience with model deployment and monitoring
• FS, lending, or mortgage exposure is a bonus, not required