Are you a Senior Data Scientist who enjoys turning complex data into intelligent, high-impact business decisions?

Join a high-performing analytics environment where you’ll design, develop and optimise Machine Learning, AI and decisioning solutions that directly influence customer experience, risk management and digital outcomes.

What You’ll Be Doing

• Design, build, train and optimise production-ready ML models using Databricks, MLflow, Python and SQL.
  
• Develop customer propensity, Next Best Action/Product, retention, engagement and customer value models.
  
• Build risk, fraud, collections and operational models that improve decision-making.
  
• Lead advanced feature engineering and develop reusable enterprise features using Databricks Feature Engineering, Delta Tables and Feature Store.
  
• Perform statistical analysis, experimentation, hypothesis testing, model validation and optimisation.
  
• Monitor model performance, drift, stability and business impact, continuously improving models.
  
• Explore and deliver Generative AI / LLM use cases where they can create meaningful business value.
  
• Partner with Product, Digital, Risk and business stakeholders to translate business challenges into scalable analytical solutions.
  
• Work closely with ML Engineers to productionise models and analytical assets.
  
• Mentor junior Data Scientists and contribute to modelling standards and best practices.
  

Requirements

Key Technologies & Expertise

Must Have:

• Strong Databricks experience – Notebooks, Workflows & MLflow
  
• Databricks Feature Engineering / Feature Store
  
• Advanced Python & SQL
  
• Machine Learning & Statistical Modelling
  
• Feature Engineering & Feature Selection
  
• Predictive & Prescriptive Analytics
  
• Model Validation, Tuning & Monitoring
  
• Experience with large-scale customer, behavioural, transactional or digital data
  

Advantageous:

• Customer Decisioning & Optimisation
  
• Risk / Fraud / Collections Modelling
  
• Generative AI, LLMs & Prompt Engineering
  
• Experience taking Data Science solutions from concept through to production
  

Qualifications

Degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, Actuarial Science, Econometrics or another quantitative discipline.

Certifications Advantageous

• Databricks Machine Learning / Data Engineer
  
• Microsoft Azure AI
  
• SAS Data Scientist
  
• AWS / Google Cloud AI & ML
  
• Recognised AI / ML / Data Science certifications