Ideate->Build->Implement->Evolve advance AI and analytics products with relevant stakeholders, including Product Manager, BA, SMEs, Data Engineers, MLEs, MLOps
• Create ML powered solutions (including Gen AI) that have business outcomes like reduced TAT, Credit process efficiencies, reduced LI for the bank through early warnings on portfolio credit health and better visibility of client profile by understanding their transactional flows and business patterns.
• Work with UX team and product managers to convert ML results to actionable outcomes. Be able to create simple dashboards for POCs.
• Develop and implement processes and solutions for model technical and functional performance monitoring, concept and data (covariate, prior probability) drift detection, user feedback-driven model improvements.
• Be responsible for ensuring adherence of solutions to Responsible AI standards. This includes representing the solution at RAI council, providing any clarifications to local compliance teams, and enabling auditability and replayability of results.
• Design, develop, and implement generative AI models and algorithms, utilizing state-of-the-art models such as GPTs, LLaMAs, and frameworks in industrial settings.
• Assess the effectiveness and accuracy of data sources and data gathering techniques.
• Identify alternate data sources (vendors and open source) with the product manager; work with data org. to onboard and integrate.
• Present proposals and results in a clear manner backed by data and coupled with actionable conclusions.
Key Responsibilities
Regulatory & Business Conduct
• Display exemplary conduct and live by the Group’s Values and Code of Conduct.
• Take personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct.
• Effectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters
Key stakeholders
• All business and Credit stakeholders that are impacted or involved with Credit Lifecycle
• Credit Transformation Programme Manager
• Credit Transformation team
• Client Coverage COO
• T&I
• Credit Policy
• Credit Process Owners
Other Responsibilities
• Leverage the opportunity provided by Corporate Social Responsibility to enhance the Group’s internal and external reputation and indirectly influence the bottom-line.
• Promote the Group’s brand and Here for good with clients and regulators.
• Perform other responsibilities assigned under Group, Country, Business or Functional policies and procedures.
• Maintain effective communication with key stakeholders, including regulators and staff.
Skills and Experience
Artificial Intelligence and Machine Learning
Understands the concepts and applications of Machine Learning (ML) in the Bank’s and/or clients’ business.
Develops, evaluation, implements and/or applies Machine Learning solutions for the continuous improvement and innovation of the Bank’s and/or clients’ processes, products, and business. Can perform data transformation, feature engineering, picking the right method to evaluate model performance (eg.. RMSE, log loss, accuracy, AU-ROC, P/R), and threshold selection based on desired outcome (eg. Sensitivity vs specificity).
Understands Responsible AI usage guidelines issues by MAS/HKMA/ECB and ensures models built are compliant (fairness, transparency, explainability, data suitability, accountability)
Programming
Proficient and hands-on on SQL, Python and PySpark; working knowledge of HiveQL, SparkML and ML libraries. Good understanding of deep learning and NLP architectures and applicability in Banking domain x
Experience working with both open source as well as vendor platforms like Databricks, , SageMaker, AzureML
Able to create simple interactive dashboard/UI to present model’s output during POC phase
Statistical Analysis
Applies systematic statistical, mathematical, and numerical analyses to interpret complex data sets to derive data-driven measurements and predictions of trends / risks
Data Analysis and Visualisation
Scopes and shapes business problems into feasible and specific data analysis problem statements. Interprets data according to defined requirements to obtain business insights, including the use of statistical and predictive modelling techniques and practices for analysis Communicates data findings and insights through data storytelling to key stakeholders through dynamic visual display of data (i.e., visual illustrations, iconographies, graphs, charts)
NLP/LLM/Gen AI
Develop, implement, and optimize large language models including finetuning using RAG and crediting Agentic AI solution.
Knowledge of cloud platforms (AWS, GCP, Azure) is a plus
Qualifications
EDUCATION GRADUATE/ PG / PHD
EXPERIENCE MIN. 10 YEARS OF WORK EXPERIENCE