Responsibilities : The Data Scientist (DS) is responsible for the end-to-end development of Machine Learning (ML) models, business intelligence (BI) dashboard automation, and data-driven strategic analysis. This role involves exploring, cleaning, and aggregating both structured and unstructured data, conducting feature engineering, performing clustering analysis, as well as model development, tuning, and validation to ensure the models meet business expectations and provide reliable insights. The candidate will also oversee the approval, deployment, and monitoring of ML models, ensuring compliance with Bank Negara and Maybank standards. Additionally, the Data Scientist will perform ad-hoc analyses to support decision-making and strategic planning based on evolving business requirements. The role requires close collaboration with cross-functional teams, including business stakeholders, risk, credit, model expert and IT teams, to deliver actionable insights and solutions that align with business objectives. To ensure that their expertise in data analysis and modelling is utilized to tackle problem statements and provide data-driven solution. Data Exploration and Analysis on datasets to identify patterns, insights and anomalies. Predictive Modelling and ML development activities such as model training on historical data, feature engineering, fine-tuning of parameters and validating of performance to ensure reliable and robust result. Experimentation and Evaluation - design experiments and conduct rigorous testing to evaluate the effectiveness of different models, algorithms and methodologies, as well as measure and compare performance metrics, assess impact of variable and iterate approaches to continuously improve results. Involve in planning, execution and deployment of Machine learning model activity.Translate MLM requirement to technical specifications. Communicate project requirement and deliverables to internal stakeholders. Liaise with Vendor on business requirements and project timeline. Assist in running scenario analyses to evaluate the potential impact of different business strategies or decisions under various conditions. Use historical data to identify emerging trends and provide forecasting insights that support future strategic planning. Collaborate with senior data scientists to apply basic time series models or regression techniques for predictive insights. Compile results from analyses into actionable insights, making basic recommendations that align with business goals and priorities. Provide data-backed support to business stakeholders to guide tactical and strategic decisions. Requirements: Bachelor&aposs degree in computer science, data science, engineering, statistical or related field. Experience in related field (i.e Statistical, Data science, Software Engineering, Banking etc) min of 2 years. Proven experience as a Data Scientist working on production models, ideally in areas of financial machine learning model development and MLOps. Advanced Python and SQL programming skills with ability to troubleshoot code and optimize scripts execution to build efficient data pipelines. Possess good communication skills. Working experience in implementing agile methodologies and practices for effective project management. Show more Show less