Develop analytical capabilities and data science algorithms that enable to do targeted marketing, optimization of processes and support other function areas of the bank. Primary focus will be in applying machine learning techniques, doing statistical analysis, and building high quality prediction and AI systems integrated with the bank’s products and functions.
Strategy and Planning
- Support Big Data analytics for MY initiatives.
- Leverage state of the art algorithms to deliver value of big data to business.
Business and Performance and Management
- Exploratory data analysis and model development using state-of-the-art methods, keeping abreast with latest developments in machine learning and applying them to solve business problems
- Selecting features, building and optimizing classifiers using machine learning techniques
- Extending company’s data with third party sources of information when needed
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
- Perform analysis and presenting results in a clear and concise manner
- Creating automated model automation to produce periodic output systems and constant tracking of its performance
- Building and integrating Large Language Model (LLMs) and LangChain into the business processes
Regulatory Compliance
- Ensures all Group Consumer operations are in compliance with Group, local and regional regulation
Qualifications
Bachelor's Degree or Professional Qualification in the relevant discipline (Financial/Engineering/Computer Science/Actuarial Science/Statistics)
Relevant Work Experience
Candidate must have at least 1- 5 years of hands on experience in statistical modeling using machine learning and AI techniques
Competencies/Skills
Technical/Functional skills
- Demonstrated experience in applying and implementing machine learning techniques such as neural networks, SVM, recommender engines, deep learning algorithms (e.g., TensorFlow, PyTorch), etc.
- Some knowledge of NLP, computer vision, and other generative AI techniques (e.g., GPT, BERT, GANs) is encouraged
- Strong knowledge of common data science toolkits like tools like R / Python.
- Experience with MLOps tools and practices, including version control, CI/CD, containerization (e.g., Docker), and orchestration (e.g., Kubernetes).
- Familiar in SQL and visualization tool such as Excel and QlikView,
- Knowledge in Big Data Tools (e.g. Hive, Impala, Hadoop and Spark) is an added advantage.
- Hands-on experience utilizing cloud base data analytics offering and services is an added advantage
Personal skills
- Ability to manage AI/ML projects, including model development, testing, deployment, and monitoring.
- Strong presentation and influencing skills required to put forward solution/ model to solve business problems
- Active team player that support various solution/ model initiatives across the bank
- Builds strong culture of excellent service and high performance
