Job Description

Role Overview:

We are seeking a highly analytical and detail-oriented Data Analyst to be part of us. The role will focus on analysing large datasets, generating actionable insights, and supporting strategic decision-making.

The ideal candidate will have strong data management skills, financial domain knowledge (Preferably Regulatory Reporting, Risk and Compliance in a corporate banking products)

, and the ability to communicate findings in a clear, business-oriented manner.

Responsibilities:

Collect, clean, and validate data from multiple banking systems (e.g., loan management, treasury, trade finance, payments). Perform quantitative and qualitative analysis on corporate banking portfolios, including lending, deposits, trade finance, and treasury products. Work with stakeholders to identify business needs and translate them into data-driven solutions. Conduct trend, variance, and scenario analysis to support pricing, profitability, and client segmentation. Ensure compliance with data governance, quality, and regulatory reporting standards. Partner with technology teams to improve data pipelines, automate reporting, and implement advanced analytics use cases.

Requirements:

Bachelor's degree in data science, Statistics, Economics, Finance, Computer Science, or a related field. Minimum 2-5 years of experience as a Data Analyst, ideally within banking or financial services. Familiarity with statistical analysis tools (Python, R) preferred. Good understanding of corporate banking products (loans, deposits, trade finance, treasury, payments). Knowledge of risk, compliance, and regulatory reporting frameworks in banking. Strong analytical, problem-solving, and critical-thinking skills. Excellent communication skills to translate technical data into business insights. Preferred Attributes Experience in data warehousing, ETL, or big data platforms (Ex: Snowflake, Hadoop, Spark). Exposure to machine learning techniques for credit/risk scoring or client segmentation. Strong business acumen with an ability to connect data insights to revenue, cost, and risk drivers. * Ability to work in cross-functional teams within a fast-paced banking environment.