Specialist, Product Operations, Reference Data

Job Purpose

The primary purpose of this position is to research, analyze, interpret, transform, and present reference data for Equity and Funds securities across global markets. The role is suited to a candidate with a data science background who can apply analytical and technical expertise to financial data operations, and who will be expected to actively contribute to the acceleration of automation initiatives across the team’s workflows.

The incumbent must successfully complete a structured two-month training program to develop subject matter expertise and gain proficiency with the database(s) of record, enabling independent analysis of legal and financial documents associated with Equity and Fund securities. Training includes assessments and accuracy/timeliness benchmarks that must be met.

The curriculum provides exposure to market structures, client use cases, and evolving financing techniques, enabling the incumbent to differentiate essential data, interpret complex terminology, and identify relevant information for downstream clients. The work directly supports ICE’s clients and internal stakeholders such as Evaluated Pricing, Index, and Analytics teams who rely on accurate and timely reference data.

Responsibilities

• Analyze, interpret, collate, and transform reference data for simple structures/events in the primary or secondary market by reviewing legal documents, vendor data, and third-party reports, ensuring accuracy, completeness, and timely delivery.
• Apply financial and legal subject matter understanding to make sound, logical decisions regarding data extraction and interpretation.
• Gather required documents by conducting advanced research and direct outreach to issuers, trustees, underwriters, and other market participants.
• Provide data and product support by responding to inquiries and conducting additional analysis where necessary.
• Identify data quality issues, trends, and gaps; maintain awareness of evolving market practices, new financing structures, and emerging terminology.
• Apply analytical thinking to drive workflow efficiency, enhance data quality, and support automation or process improvements.
• Take an active role in accelerating the team’s automation agenda by developing scripts, tools, and repeatable solutions that reduce manual effort and improve throughput.
• Build and maintain automated data extraction, transformation, and validation pipelines that support production workflows and scale with increasing data volumes.
• Collaborate with the Operations Manager and wider team to scope, prioritise, and deliver automation improvements that have measurable impact on productivity and data quality.
• Participate in ad hoc initiatives focused on optimizing processes, improving data completeness, and supporting automation opportunities.
• Communicate professionally with external market participants to obtain reference data, resolve discrepancies, and clarify terms or ambiguous content.

Knowledge and Experience

• Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related quantitative discipline; equivalent professional experience will be considered
• 5+ years of corporate-level experience, or 2+ years of direct experience in reference data, financial operations, market data, or a related domain
• Strong data science foundation with demonstrable experience applying analytical and technical methods to real-world data problems
• High attention to detail and ability to interpret complex legal/financial documentation
• Strong analytical, decision-making, and problem-solving abilities
• Ability to work effectively in a fast-paced, dynamic environment
• Strong Excel skills, including functions, formulas, and data handling
• Ability to convert large datasets into concise, actionable insights
• Eagerness to learn, collaborate, and adapt to evolving market requirements

Preferred Skills

• Proficiency in Python for data automation, scripting, and workflow development
• SQL skills for data querying, reconciliation, and validation against production databases
• Excel Macros and VBA development for task automation and process efficiency
• Experience with web scraping tools and techniques for automated data collection
• Familiarity with Anthropic AI (Claude) or other large language model (LLM) platforms applied to data workflows
• Exposure to AI, automation, or machine learning concepts within an operational context
• Proficiency in the Portuguese language, particularly for processing Latin American securities documentation
• Additional proficiency in the Spanish language would be an added advantage