Data Operations Strategy - Analyst

Data Operations Strategy Analyst

As a Data Operations Strategy Analyst within the Instrument Reference Data team, you will work at the intersection of data, operations, and business—translating complex data problems into practical, scalable solutions that improve how the bank operates. This is a role for someone who is comfortable with ambiguity. You will identify and frame problems as they emerge, prioritize what matters most, and build analytical tools and dashboards that help teams make better decisions. You will partner closely with stakeholders across trading, operations, and reporting to diagnose data quality issues, understand their root causes, and deliver targeted fixes.

Job Responsibilities

• Identify and frame incoming data and operational challenges, prioritize what matters most, and define practical strategies to address them.
• Design and build data solutions using visualization tools, SQL, Python, and AI-enabled platforms to support operational metrics and analytics.
• Contribute to data quality initiatives end-to-end—from problem identification through delivery and scaling—working closely with senior team members.
• Perform root-cause analysis to uncover process inefficiencies and implement targeted improvements that reduce recurring data issues.
• Facilitate stakeholder discussions to gather requirements, align on priorities, and track progress on data quality initiatives.
• Collaborate with data teams across regions to support day-to-day data activities and maintain quality standards.
• Ensure solutions are documented and aligned to internal controls, with awareness of associated operational and reputational risks.

Required Qualifications, Capabilities, and Skills

• Bachelor's degree.
• Minimum 1 year of experience in a data, operations, quantitative, or analytical role within financial services.
• Strong analytical and problem-solving skills, with the ability to break down complex challenges and deliver practical solutions.
• Ability to work independently in an ambiguous environment, managing competing priorities and knowing when to escalate.
• Strong communication skills—able to work across teams and seniority levels, extract requirements, and keep stakeholders aligned.
• Proficiency in SQL and Python for data analysis and automation.
• Hands-on experience with at least one visualisation tool (Power BI, Tableau, or Qlik) and at least one workflow or project management tool (Jira or Confluence).

Preferred Qualifications, Capabilities, and Skills

• Experience with Alteryx or similar data preparation and workflow automation tools.
• Familiarity with AI or machine learning tools applied to data quality, classification, or operational workflows.
• Experience with RPA tools such as UiPath.
• Understanding of data management principles in financial services, including governance, quality, lineage, and modelling.
• Knowledge of financial instruments, corporate action events, and data vendors such as Bloomberg, Refinitiv, ICE, or MSCI.

Shape data strategy and solve real operational problems at the intersection of data, business, and product.