A leading bank is seeking to expand its analytics capability and is recruiting a Data Analyst for its core analytical team. The role is responsible for producing high-quality analytical insights and supporting the configuration, implementation, and optimization of machine learning models. The position is aligned with global, data-driven initiatives, including churn prediction, customer segmentation, and behavior-based analytical frameworks.

Responsibilities

• Perform advanced analyses on large-scale datasets to deliver actionable insights to business and product stakeholders

• Contribute to the design, configuration, and operationalization of machine learning models, including churn, segmentation, and behavioral prediction models

• Utilize Python and SQL to create analytical datasets, conduct statistical assessments, and prepare model-ready data structures

• Develop, maintain, and enhance dashboards and analytical assets using Looker, BigQuery, and cloud-based BI technologies

• Collaborate with cross-functional teams to define and monitor KPIs across customer lifecycle and operational processes

• Execute deep-dive analyses in areas such as credit risk, campaign effectiveness, churn dynamics, and growth opportunities

• Ensure adherence to data quality standards, metadata management, and documentation requirements

• Work closely with Data Scientists, Data Engineers, and global partners to support analytical and modeling outcomes

Qualifications

• Bachelor’s degree in Statistics, Mathematics, Computer Engineering, or another analytical discipline

• Advanced proficiency in SQL

• Strong capability in Python and key analytical/ML libraries (pandas, numpy, scikit-learn)

• Experience with Looker, BigQuery, or comparable cloud-based BI and data technologies

• Understanding of the machine learning lifecycle and ability to support model deployment and monitoring activities

• Prior exposure to churn analytics, segmentation methodologies, lifecycle analytics, or predictive modeling is highly desirable

• Strong analytical thinking, structured problem-solving ability, and the capacity to convert complex data into business insights

• Excellent command of English (written and verbal)

• Ability to operate effectively within a global, multi-stakeholder, and technology-intensive banking environment