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Data Quality Analyst
7 months ago
At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways.
If you are excited about this opportunity but do not meet every single requirement, please apply You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
Department:
The Predictive Analytics group transforms our data into state-of-the-art analytics to help clients make better decisions in the face of uncertainty. Our clients come from a wide range of industries such as banking, insurance, commercial real estate and many more. They use our economic research to evaluate credit-worthiness, to monitor risks and opportunities when weighing up major investment decisions as part of their corporate strategy. Our team is made up of intellectually curious economists, data scientists, and IT professionals who combine technical skills with a strong desire to understand clients’ needs.
Role/Group:
As a Data Quality Analyst, you will have the opportunity to contribute to a team responsible for generating and delivering industry leading risk metrics to a variety of products offered by Moody’s Analytics. The Data Quality Analyst may perform a variety of different data management job functions, including data acquisition, data processing, data operations, with focus on data quality and driving data insights. This position involves a blend of qualitative/quantitative financial research and technical skills to source and maintain credit risk data and models. This position is for you, if you are a quick learner, have a passion for data to identify trends, uncover patterns, understand credit risk models, solve problems and your favorite question is ‘why’.
The Corporate Credit Data group is responsible for managing the critical processes that ensure the accuracy and timely delivery of vital financial data that is linked to our industry-standard credit risk measurement tools and related software applications. This role will facilitate that process, working with the engineering, IT, support, and development teams to ensure the timely and seamless delivery of data to clients. Additionally, the role is responsible for gathering and inputting financial data from clients into the company’s credit risk measurement tools and software, as well as running the data processing and calculations that feed the company’s credit risk measurement and management products.
Responsibilities:
• Monitor and analyze data quality trends, and develop strategies to improve data quality over time
• Develop and maintain data quality metrics to measure the effectiveness of data quality processes
• Design and implement data quality monitoring and reporting processes to ensure ongoing data accuracy and consistency.
• Conduct data profiling and analysis to identify data quality issues and recommend solutions.
• Build and maintain data processing and calculations to feed MA’s credit risk measurement and related products/models
• Efficiently extract financial information and equity data from publicly available reports of companies for conducting thorough validations to compare and reconcile data obtained from external vendors with information sourced from public disclosures.
• Map financial line items from company reports to specific model inputs. Apply data transformation techniques to standardize and prepare data for analytical processing. Stay updated with financial reporting standards to accurately interpret and categorize financial information.
• Identify ways to improve data operations processes either by automation or other means
• Build data model for input and output of credit risk models
• Perform data analysis using a variety of methods including statistics and relational databases
• Perform quality control on data by analyzing patterns and data discrepancies and resolve related issues
• Produce reports using Business Intelligence tools that describe data characteristics and highlight trends and issues
• Contribute towards documentation of the processes/projects as they near completion
• Develop and implement AI-powered data quality strategies to improve the accuracy, completeness, and consistency of our data assets.
• Support and resolve data inquiries and issues with accuracy and in a timely manner
Qualifications:
• Requires Bachelor’s degree in Economics, Statistics, Finance, Accounting, Operations, Engineering or a related field.
• Graduate degree and/or 1-2 years of work experience is a plus.
• Superb analytical skills, persistence in problem solving, and ability to learn quickly and independently
• Strong organizational skills, attention to detail, and ability to manage multiple projects with tight deadlines
• Strong logical thinking that can develop robust code for data analysis and QC process
• Excellent written and oral communication skills
• Exposure or interest in financial services space
• Ability to correctly read and interpret financial statements such as 10K and 10Q; US GAAP, IFRS, and other regional accounting principles
• Experience working with AWS (Glue, Athena)
• Experience working with Large Language Models
• Proficiency in SQL (SQL Server, PostgreSQL, MySQL)
• Strong attention to detail and accuracy
• Proficiency in a statistical package (R),
• Experience with a scripting language (Python)
• Proficiency in MS Office, especially MS Excel
Preferred:
• Exposure to third-party BI Tools: Tableau, Qlik, R Shiny
• Exposure to ETL tools: CloverETL
• Experience working with major financial data feeds
• Experience in data modeling and query optimization
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.
