Job Description

• Build Machine Learning models on the big data platform to increase marketing ROI and lower the cost of acquisition by developing propensity models for bankwide team (Consumer, COBA, COMBA, EBB, Risk, Operations, AML, Fraud etc.)
• Partner with Product, Sales, and Channel teams in bankwide segment in understanding the product, channel, segment and custom build statistical solutions with speed to market
• Develop cross-sell and upsell models to deepen share of wallet with existing customers
• Deliver statistical models with quality on time, in line with business priorities
• Capitalize structured /unstructured data and data science technique to develop big data use cases in multiple bankwide area
• Designs and implements big data use cases to support the business initiatives and programs
• Track the business’s performance against model and monitor trends in key business KPIs, providing valuable insights to relevant departments for overall business performance improvement

Competencies and Skill Requirements

• Having 1-3 years of working experience
• Exposure or have working experience with Big Data Platforms (onprem or cloud based i.e: Hadoop, Hue, Google Cloud Platform, AWS, Azure, etc), inclusive of machine learning development, experimental design, and optimization
• Strong experience in building predictive model and/ or data science project
• Modeling experience with Python
• Solid critical thinking and analytical skills to work well with numbers and complex data
• Keen to learn about Bankwide product and if already have strong banking domain knowledge is a plus
• Translate and communicate modeling result to business users