Assistant Director - Data Operations

Job Description The data operations 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 risk and performance measurement tools and related software applications. This role will facilitate that process, working with the IT, support and development teams to ensure the timely and seamless delivery of data to clients. Additionally, the role is responsible for analyzing the data processing and calculations that feed the company's products as well as analyzing data from potential data providers.

Responsibilities:

• Gather financial data from banks/clients/financial institutions and external data vendors, including exploration of new data sources, and engaging in conversations with prospective data partners along with Sales team
• Analyze the data processing and calculations that feed the company's risk and performance measurement products.
• Design new processes for cleansing/standardizing data from multiple sources for input into a centralized database.
• Identify, research and resolve issues involving financial data errors during data processing and calculations, and coordinate with other teams such as IT, support and development to resolve any data processing or client issues.
• Analyze data from potential data providers.
• Publish documentation designed to inform and assist clients and prospects in understanding the company's data offerings.
• Manage data relationships and provide customer support/feedback to banks/clients/financial institutions/internal clients and feedback to external data vendors
• Collaborate with internal and external data partners on contractual, service and usage issues.
• Regularly report data-related and technical issues to data providers.
• Provide internal support to the firm's staff regarding daily data processing and calculations.
• Provide constructive feedback and assistance to the management, IT, support and application development teams on existing and new data processing systems and products.
• Lead small exploratory data science/analytic projects; identify market trends for new analytics in reports
• Work schedule requires some evening shifts, once a month weekend shifts and some holiday shifts.

Qualifications

• Undergraduate/first-level degree (i.e., Bachelor's degree) in Operations, Management, Engineering, Accounting, Finance or a related field.
• CFA/CRM qualifications preferred.
• Experience in finance, economics or business.
• Experience with reference (i.e., terms and conditions) and time series data used in performance attribution or market risk analytics preferred.
• Proficient in MS Excel.
• Strong proficiency in SQL (Sybase, Microsoft SQL server, SAS), Microsoft Excel and Access.
• Exposure to Java, C++ or Visual Basic is a plus.
• Superb analytical skills and persistence in problem solving.
• Proficiency in a statistical package (R, SAS, Matlab)
• Proficiency with BI and ETL tools
• Strong organizational skills, attention to detail and the ability to manage multiple projects with tight deadlines.
• Excellent written and oral communication skills.
• Experience documenting standard operating procedures preferred.
• Strong understanding of pricing concepts for various financial instruments e.g. equities, bonds, derivatives.,
• Knowledge of interest-rate modelling, and curve construction.
• Familiarity with data vendors, preferably Refinitiv.

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.