Job Responsibilities :
- Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as Explainable AI, predictive time series analysis and recommendation systems
- Choose, extend, and innovate ML strategies for various banking problems
- Collaborate with multiple partner teams such as Business, Technology, Product Management, Strategy and Business Management to deploy solutions into production
- Learn about and understanding our supported businesses in order to drive practical and successful solutions
- Solve explainable problem, develop production prediction models, and manage ML Ops
Required qualifications, capabilities, and skills
- Formal training or certification on AI ML concepts and 2+ years applied experience
- Good understanding of the latest advancement of Explainable AI concepts.
- Experience in classical ML techniques including classification, clustering, optimization, cross validation, data wrangling, feature selection, and feature extraction
- Ability to design experiments — establish strong baselines, choose meaningful metrics, and evaluate model performance rigorously
- Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
- Solid written and spoken communication skills
Preferred qualifications, capabilities, and skills
- Experience, as a Data Science lead, in driving projects end to end is preferred
- Experience in LLM, building RAG pipeline is preferred
- Experience in large scale Machine Learning system design is preferred
- Experience working with end-to-end pipelines consisting of Cloud services is preferred, preferably, with AWS ML ecosystem (i.e. SageMaker, etc.)
- GPU is preferred