Job Purpose
Development of AI use cases by utilizing machine learning and/or advanced analytics methodologies for objectives such as revenue growth, cost reduction, and productivity enhancement across all bank partners. Act as a strategic business partner for stakeholders throughout the bank by identifying and pursuing new initiatives and actionable insights by leveraging internal and external data sources.
Key Responsibilities
- Develop & deploy Advanced Analytics models on the big data platform to increase marketing ROI and lower the cost of acquisition by developing propensity models for bankwide teams (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 areas bankwide
- Work and Collaborate with Data Science Head/Team to deliver AI use cases
- 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
- Develop a more effective and targeted cross selling initiatives through the use of Big Data capability data and utilizing more unstructured data (i.e: Weblogs, cookies, social media, etc)
- Full compliance with CIMB Niaga's procedure, guidelines, working instruction and other regulatory requirements
- Adhere to data information security guidelines for any sensitive records or information
- Full responsibility
Technical/Functional skills
- Strong understanding of data science, advanced analytics, machine learning, and/ or generative ai concepts with the ability to develop until deployment of AI/ ML initiatives across the bank.
- Hands-on experience of advanced analytics solutions on Big Data and Cloud platforms (e.g. Hadoop, Spark, AWS, GCP, Azure), using both structured and unstructured data.
- Proven capability to review, guide, and govern the development and deployment of advanced analytics and machine learning models, ensuring quality, scalability, and sustainability.
- Solid knowledge of statistical methods, with the ability to ensure appropriate techniques are applied to business problems.
- Strong awareness of model risk, data governance, and regulatory requirements in a banking or financial services environment.
- Ability to translate complex data and analytical outcomes into clear business insights and measurable business impact.
- Proficient in overseeing analytics work developed using Python, SAS, SPSS, R, and SQL, focusing on standards and best practices.
- Strong banking and financial services domain knowledge, enabling effective collaboration across Risk, AML, Fraud, Marketing, Operations, and Customer Experience.
Qualifications:
- Bachelor's degree
- Minimum 3 year of banking/financial services experience in Data Science/Machine Learning, Analytics role, and Big Data used case implementation
- Proficient in English as a business language and in Microsoft Office applications (Excel, PowerPoint) for executive‑level communication.
- Excellent analytical thinking, problem‑solving, and decision‑making skills.
- Good communication skills i.e. presentation and influencing skills
- Strong ability to build partnerships across functional teams through collaboration
