Job Description
This role demands a hands-on technical leader capable of mining vast, unstructured financial datasets to build production-grade machine learning solutions. You will own the full data lifecycle—from initial mining and feature engineering to model training, validation, and deployment. Beyond coding, you will set the standard for statistical rigor within the team, ensuring our models remain accurate, explainable, and compliant with financial regulations. You will apply advanced statistical techniques to tackle our toughest challenges in personalisation and default prediction, understanding our customers among others.
Qualifications
Type of Qualification: First Degree
Field of Study: Degree in Information Technology, Computer Science, Actuarial Science, Statistics, Mathematics, Economics or any other related field.
Experience Required
Data & Analytics 4-7 years
- Experience in working with unstructured data (e.g. Streams, images) Understanding of data flows, data architecture, ETL and processing of structured and unstructured data. Using data mining to discover new patterns from large datasets. Implement standard and proprietary algorithms for handling and processing data. Experience with common data science toolkits, such as SAS, R, SPSS, etc.
- Experience with data visualisation tools, such as Power BI, Tableau, etc.
- Proficiency in application of Structured and Unstructured Query languages e.g. SQL, Python, Power Query; QlikView; Tableau; R.
- Proven understanding of financial services data processes, systems, and products. Experience in technical business intelligence. Knowledge of IT infrastructure and data principles. Project management experience.
- Experience in building predictive models (credit scoring, propensity models, churn prediction, product recommendation, etc.)
- Candidates must demonstrate a strong and successful track record of leading high-performing data analytics teams, driving impactful business outcomes through advanced quantitative analysis and statistical modelling.
- Experience managing stakeholders translating technical concepts for business heads and executives.
Additional Information
Behavioural Competencies:
- Analytical Thinking
- Challenging Ideas
- Excellent Communication Skills
- Interpreting Data
- Team Player
Technical Competencies:
- Python (Pandas, NumPy, Scikit-learn)
- Relational and No SQL/Vector Databases
- ML/AI Orchestration Frameworks
- Machine Learning Model Development
- Research & Information Gathering
