Audit Data Science

We are looking for a data scientist who will work in the Internal Audit area and is 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) to build models that support and provide 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
• Improving the efficiency of various technical operations within 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 degree in computer science, statistics, physics, mathematics, or other related fields. An advanced postgraduate degree and ancillary courses in finance, economics, actuarial sciences, and related disciplines would be valued.
• Understanding of the theoretical foundations underpinning machine learning and deep learning models, along with hands-on experience dealing with real-world problems.
• A minimum of 7 years of work experience with at least 3 years of experience deploying machine learning in production environments and at least 3 years of experience building machine learning and deep learning models.
• Core competencies and experience as a data scientist, including statistical analysis, machine learning, computer science, numerical analysis, and software engineering. Proficiency in programming languages such as Java, R, Python, SQL, and other computing tools for analyzing large datasets and solving complex problems.
• 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 not a requirement.
• Strong communication skills to effectively convey complex ideas to less technical audiences.

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