About the Role :
We are looking for a data scientist who will work in Internal Audit area and familiar with a broad spectrum of modeling techniques (both classical ML and various deep learning modeling approaches) utilizing a wide variety of data types (e.g. transactional financial data, system log data, clickstream data, geospatial data, customer support chat log, audio recordings, image and video data, etc) to be able to build models that support and providing assurance on:
- Digital banking product features such as smart financial recommendations around how much to save and when
- Optimization of growth and marketing functions such as dynamic content and marketing recommendations to customers
- Business operations optimization
- Real-time fraud detection and other risk management functions
- Credit risk management
- Improving the efficiency of various technical operations with the business
- Data integration and cleaning from diverse sources
- Ensuring the explainability and interpretability of models
- Implementing anomaly detection techniques for identifying irregularities
What You Need to Have :
- A Bachelor’s, computer science, statistics, physics, mathematics or other related degree. Advanced postgraduate degree and ancillary degrees or courses in finance, economics, actuarial and related disciplines would be valued.
- Understands the theoretical foundations underpinning machine learning and deep learning models while also has hands-on experience dealing with the problems they throw up in the real world.
- Min 7 years work experience with min 3 year experience deploying machine learning in production environments and min 3 years building machine learning and deep learning models.
- Having core competencies and experiences of data scientist, i.e.: Statistical analysis, machine learning, computer science, numerical analysis, and software engineering. Programming: Write computer programs and analyze large datasets to uncover answers to complex problems. Comfortable writing code working in a variety of languages such as Java, R, Python, SQL and other computing tools.
- Familiarity with advanced analytics and business intelligence tools for audit reporting.
- Experience with cloud platforms (e.g., AWS, GCP, Azure) for deploying models and managing large datasets.
- Experience with CI/CD tools and practices to streamline the deployment and updating of models and applications.
- Experience with financial modeling of moderate complexity is desirable, but is not a requirement.
- Strong communication skills are essential to help communicate complex ideas to less technical audiences.
