VP, Senior Data Scientist, Institutional Banking Group Operations, Technology & Operations
Corporate and Investment Banking provides corporate customers with a full range of commercial banking products and services, including cash management services, current accounts, time deposits, trade finance, working capital finance, term loans and foreign exchange. Through our continued commitment, DBS has cultivated long-standing relationships with its customers in the region that are based on account relationship management, service differentiation, product development and rigorous credit standards. Responsibilities
- Maximize Data capabilities focusing on customer/ employee science in areas such as predictive/ prescriptive/ text analytics across corporate banking products / processes and customer servicing (Chatbot & other digital channels).
- Deliver analytics initiatives to address business problems with the ability to determine data required, assess time & effort required and establish a project plan. To manage other digital instrumentation projects undertaken by the team, and be accountable for their delivery (includes planning, prioritization, scope, risk / issues management)
- Conduct strategic data analysis, identify insights and implications from institutional data and make strategic recommendations to executive and senior staff, develop data displays that clearly communicate complex analysis
- Test the solution with real live data & present the results to senior management for approvals
- Implement the solution and support the Technology team to deploy the solution to production
- Facilitate to drive up adoption / embedding data in use of operations/ servicing/ journey design
- Highly self-driven and operate under "Agile" methodology & able to perform end-to-end development from requirements gathering, to design, development, testing and deployment.
- Prepare project updates report and communicate projects benefits & progress to management team or business stakeholders
- Engage with the broader analytics community within the bank and align with the overall strategy / direction undertaken by the bank.
- Create reusable assets and share learning with others
Apply Now We offer a competitive salary and benefits package and the professional advantages of a dynamic environment that supports your development and recognises your achievements.
- PhD or Masters or equivalent degree in Statistics, Applied Mathematics, Operation Research, or equivalent quantitative fields preferred. Strong mathematical and statistics background is preferred.
- 4-6 years of experience in industry (ideally banking, ecommerce, telecoms, retail) and/or academia with demonstrated track record of innovative research and insight generation and implementation of insights into tools/processes delivering front end business result
- At least 5 years of data mining and machine learning on large amount of data, building and implementing various statistical models.
- Good understanding of technology tools especially those related to analytics, data & statistical modelling.
- Have developed and implemented industrial standard machine learning solutions for classification, prediction, text mining and anomality detection problems.
- Familiarity with a wide range of statistical analysis, machine learning, natural language processing and deep learning techniques.
- Expertise in machine learning and data mining with excellent data processing, wrangling and feature engineering skills. Familiarity with industry paradigms and standards for model development, validation and testing.
- Strong theoretical understanding and practical knowledge and be able to apply the appropriate solution framework for different modelling tasks that forms the analytic solutions.
- Ability to push the boundary of advanced analytics/machine learning/artificial intelligence to the extent of implementing newly proposed algorithms from research papers if necessary.