Job Description

Job Title: Reference Data Operations Analyst / Reference Data Analyst

Comp: 150-500k total compensation (candidate dependent)

Ideal YOE: 3-15 years

Summary: A successful hedge fund is looking to bring on a qualified candidate in the reference data operations or data analysis space. A qualified candidate will have experience with reference and market data as well as SQL/Python.

Responsibilities

• Troubleshoot and resolve data discrepancies, monitor vendor SLAs, and communicate data issues to internal stakeholders.
• Implement proactive measures to identify and resolve data issues automatically.
• Handle internal client requests and inquiries, ensuring transparent support and leading communication on any SLA breaches.
• Assist in the onboarding of new datasets, validation rules, and user interface improvements, as well as participate in testing.
• Discover, source, validate, and drive the on-boarding of new data-sets that enable unique investment opportunities, working across internal teams and external vendors
• Create and maintain internal data library that collates information internally and externally on an ongoing basis
• Work with technologists, project managers, and business analysts to deliver reference data system upgrades
• Develop and document standardized processes for data support, monitoring, and quality assurance.
• Collaborate with global team members to ensure seamless transitions between support regions.
• Follow and maintain a daily playbook of operational procedures and controls
• Capture all metadata feeding into an Incident Management program for all reference data issues
• Produce operational reports for team and management reviews on a regular basis

Qualifications

• Experience in financial services, asset management, or hedge funds with a focus on data operation and reference data support.
• Expertise in reference data content from common financial service data providers such as Bloomberg, Refinitiv, Barra, FactSet, etc.
• Experience troubleshooting and resolving data issues, along with experience in engaging with data consumers.
• Programming skills in SQL and Python.
• Experience working with large data sets.
• Strong analytical and problem-solving skills, with a keen attention to detail.
  

Desired Skills and Experience

reference data
market data
pricing data
eod pricing
financial services
python
sql
client data
security master
security data
pnl

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