Data Operations Analyst – Reference Data

Point72 Asset Management, L.P
London
2 weeks ago
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About

We are passionate about data. We collaborate to build elegant, effective, scalable, and highly reliable solutions to empower predictive modelling in finance.

Cubist’s data services group is looking for a Data Operations Analyst to join our dedicated team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world.

This exceptional individual will join a global team of analysts who monitor, validate, and support Security and Issuer reference data within the firm’s central reference data system.


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.
  • Develop and document standardized processes for data support, monitoring, and quality assurance.
  • Collaborate with global team members to ensure seamless transitions between support regions.
  • Liaise with Business, Technology, and Operations leadership to ensure alignment on project objectives, deliverables, requirements, and status updates.


Requirements

  • Bachelor’s degree with a concentration in Computer Science or related discipline.
  • 3+ years of 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 oral and written communication skills.
  • Strong analytical and problem-solving skills, with a keen attention to detail.
  • Commitment to the highest ethical standards.

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