AVP / Senior Associate, Machine Learning Engineer, CBG Business Analytics, Consumer Banking Group
As the leading bank in Asia, DBS Consumer Banking Group is in a unique position to help our customers realise their dreams and ambitions. As a market leader in the consumer banking business, DBS has a full spectrum of products and services, including deposits, investments, insurance, mortgages, credit cards and personal loans, to help our customers realise their dreams and aspirations at every life stage. Our financial solutions are not only the best in the business - they were made just right for you. Responsibilities
Deploy machine learning models, data science solutions and working with state-of-art data science and machine learning tools such as Spark, Sklearn, Tensorflow and will have mastery in any number of analytic programming languages/platforms like Python, R. etc. Work with large datasets, distributed Big Data Platforms, CI/CD tools for continuously deploying variety of advanced analytics solutions across the bank ranging from recommendation engines, propensity models, customer segmentation, Graph models, Credit underwriting model, pricing and more Engage with data science/machine learning project teams, business and product teams to create the deployment framework Involved in end-to-end processes for model deployment and model performance monitoring Deploy A/B test experiments to test the model effectiveness and analyze to identify the target segments Drive the big data infrastructure/ data engineering team to set up the production environment Build reusable, scalable deployment frameworks Requirements
3-7 years of experience in data science/analytics (consumer banking, ecommerce, retail, telecoms, technology) with demonstrated track of generating value through DS/ML/AI solutions. B.Sc./M.Sc./PhD or equivalent degree in Statistics, Analytics, Applied Mathematics, Operation Research, or equivalent quantitative fields preferred. Should have full understanding of applications of DS/ML/AI solutions to various business problems. Proficiency in using databases like Teradata, NoSQL and Hadoop using SQL, Hive, Spark, CI/CD tools such as Bitbucket/GitHub, Jenkins, Repository management, Kubernetes, Kibana, Grafana etc. and project management tools such as JIRA Programming experience in Python, Spark, SAS, TensorFlow or other machine learning oriented programming languages/platforms. Good understanding of technology tools especially those related to analytics, data & modeling. Ability to communicate complex analysis/models across a diverse team. Good written and oral communication skills. 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.