Database Engineer 1 – Quantitative Research Group - Prague - 18215BR

Moody's is an essential component of the global capital markets, providing credit ratings, research, tools and analysis that contribute to transparent and integrated financial markets. Moody's Corporation (NYSE: MCO) is the parent company of Moody's Investors Service, which provides credit ratings and research covering debt instruments and securities, and Moody's Analytics, which offers leading-edge software, advisory services and research for credit and economic analysis and financial risk management. The Corporation, which reported revenue of $4.4 billion in 2018, employs approximately 13,100 people worldwide and maintains a presence in 42 countries. Further information is available at
Moody’s Analytics provides financial intelligence and analytical tools supporting our clients’ growth, efficiency and risk management objectives. The combination of our unparalleled expertise in risk, expansive information resources, and innovative application of technology, helps today’s business leaders confidently navigate an evolving marketplace.


Moody’s Analytics’ Content Solutions-Economics and Consumer Credit group is the premiere, independent provider of economic, financial, country and industry research designed to meet the diverse planning and information needs of businesses, governments, and professional investors worldwide.

Job Description

The Quantitative Research Group is a fast-growing, hands-on development and operations team responsible for data estimation, algorithmic analytics, data management and process improvement. The group conceives, designs, implements, and operates algorithms to produce unique client-facing data sets. The team also engineers’ tools and processes to achieve leaps forward in productivity and quality.

The Database Engineer 1 role manages and develops client-facing estimated, analytical, and value-added data sets. Tasks include developing estimation algorithms, programmatic implementation, continuous improvement, data management, and documentation. The Database Engineer 1 also seeks to improve the productivity and quality of processes and analytical programs. The role also serves as a subject matter expert for their datasets, supporting clients, sales, and colleagues on their use, methodology, and interpretation.
  • Develop innovative data products from large data sets
  • Design and implement data processing operations
  • Identify opportunities and execute programmatic solutions to improve productivity
  • Applying analytical skills to interpret business functions, understand functional requirements, and research and resolve system problems.
  • Contribute to the ongoing development of standards and best practices


Minimum education and work experience required for this position include:
  • BA or BS degree with course work in economics, finance, statistics, or related fields
  • Excellent academic record
  • Numerical or statistical programming experience
  • Knowledge of foreign languages is preferred, but not required

To be successful, a candidate must possess
  • Superior analytical skills problem-solving ability
  • Structured reasoning, balancing attention to detail with effective execution
  • Excellent communication and interpersonal skills to work effectively with clients and colleagues
  • Motivation and initiative to take responsibility and make independent, well-reasoned decisions
  • Judgment and capability to manage uncertainty
Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.