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.
RequirementsKey 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
If you’re passionate about Machine Learning, AI and building data-driven solutions at scale, this is an opportunity to make a real impact.
Desired Skills:
- Databricks
- MLflow
- Python
- SQL
- Machine Learning
- Statistical Modelling
Desired Qualification Level:
- Degree
About The Employer: