Job Responsibilities:
- Collaborate with teams of Business Analyst and Data Analyst in conducting comprehensive analyses of banking data, including customer transactions, product performance, customer behaviour, market trends, etc.
- Develop and implement data-driven strategies to optimize new product creation, customer acquisition, customer retention (anti-attrition), and cross-selling opportunities within banking portfolio.
- Collaborate with business units and senior leadership to identify key performance metrics, KPIs, and benchmarks to track and measure business performance.
- Conduct hands-on and utilize statistical techniques, predictive modelling, machine learning etc, to forecast business trends (including funding and lending), assess risk such as credit risk, and support decision-making processes.
- Partner with IT and data engineering teams to ensure data quality, integrity, and availability for analysis purposes.
- Provide strategic recommendations based on data insights to enhance product offerings, pricing strategies, and operational efficiency.
- Stay attuned on industry trends, regulatory changes, and competitive landscape affecting the banking sector in relevant countries, to inform data analysis and strategic initiatives.
- Adopt data visualization and present findings and recommendations to senior executives and stakeholders in a clear and compelling manner and influence strategic decisions.
Job Requirements:
- Bachelor’s degree in Statistics, Mathematics, Economics, Business Administration, or a related field.
- Min. 8 years of experience in data analysis, business intelligence, or related roles within the banking industry.
- Strong proficiency in SQL, Python/R, and data visualization tools (e.g., Tableau, Power BI) for analyzing large datasets and creating insightful visualizations.
- Proven track record of delivering actionable insights and recommendations through data analysis to drive business growth and operational efficiency in banking.
- Deep understanding of retail banking products, services, customer lifecycle, and regulatory environment.
- Familiarity with data governance principles and practices, ensuring compliance and data integrity in analytical projects.
- Previous experience in leading cross-functional teams and collaborating with stakeholders across different departments.
- Excellent communication and presentation skills, with the ability to translate complex data analysis into clear and concise business implications.
- Experience with machine learning techniques and advanced analytics (e.g., clustering, regression, decision trees) applied to banking data, is a plus.
