Data Quality & Analytics Analyst for Risk Data

Moody's Investors Service

Singapore

Hybrid

SGD 60,000 - 90,000

Full time

6 days ago
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Job summary

Moody's Investors Service is seeking a Data Quality Analyst to join our Analytics team in Singapore. The role focuses on investigating, testing, and stabilizing data pipelines to ensure timely, accurate delivery across multiple client-facing platforms and products.

The ideal candidate will analyse financial and credit risk data, build models, and collaborate with Research, Engineering, and Product teams. A strong foundation in SQL, Python, cloud platforms, and BI tools will help drive

Qualifications

  • Bachelor's degree in Economics, Statistics, Finance, Accounting, Operations, Engineering, or related field.
  • Graduate degree and/or 1-2 years of relevant work experience is a plus.

Responsibilities

  • Investigates, troubleshoots, and tests data pipeline and content issues to ensure accurate, timely data delivery across client-facing platforms and products.
  • Support and resolve data quality and delivery issues related to complex credit risk models and data pipelines with accuracy and in a timely manner.
  • Fulfill data delivery and data requests for existing and prospective clients accurately and in accordance with deadlines.
  • Respond to client data queries timely and engage in collaborative problem solving with Customer Success and Client Support teams.
  • Support Data Engineering and Data Quality teams in monitoring data delivery and pipeline status.

Skills

SQL
Python
AWS
ETL tools
Data analysis
Communication
Excel

Education

Bachelor's degree in Economics/Statistics/Finance/Accounting/Operations/Engineering
Graduate degree or 1-2 years experience a plus

Tools

SQL Server
PostgreSQL
Tableau/Qlik/AWS QuickSight

Job description

Moody's Investors Service is seeking a Data Quality Analyst to join our Analytics team in Singapore. The role focuses on investigating, testing, and stabilizing data pipelines to ensure timely, accurate delivery across multiple client-facing platforms and products.

The ideal candidate will analyse financial and credit risk data, build models, and collaborate with Research, Engineering, and Product teams. A strong foundation in SQL, Python, cloud platforms, and BI tools will help drive

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