Data Analyst - Corporate Banking, Regulatory Reporting

RAPSYS TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 50,000 - 70,000; Full time

Job summary

A technology firm in Singapore is looking for a Data Analyst to focus on corporate banking regulatory reporting. The ideal candidate will have a Bachelor’s degree and 2-5 years of banking experience, with skills in data analysis and knowledge of banking products. Familiarity with statistical tools like Python or R is preferred. This role involves working with cross-functional teams to derive insights from data.

Qualifications

• Minimum 2–5 years of experience as a Data Analyst, ideally within banking or financial services.
• Knowledge of risk, compliance, and regulatory reporting frameworks in banking.
• Familiarity with data warehousing and ETL processes.

Responsibilities

• Perform regulatory reporting and data analysis.
• Automate processes using analytics tools.
• Translate technical data into actionable business insights.

Skills

Data analysis

Statistical analysis tools (Python, R)

Corporate banking knowledge

Analytical and problem-solving skills

Communication skills

Education

Bachelor’s degree in data science, Statistics, Economics, Finance, Computer Science

Tools

Snowflake

Hadoop

Spark

Job description

Role: Data Analyst - Corporate Banking, Regulatory Reporting

JD:

data analyst - Regulatory Reporting - automation and analytics tools on regtech

Required Skills & Qualifications

• 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.