Business Analyst - Capital Markets

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 1000 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning and AI. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are seeking an experienced Capital Markets Business Analyst to support initiatives across Data Foundation & Analytics reference data, market data, and trade lifecycle processes. The ideal candidate will have strong capital markets domain expertise, hands-on data analysis skills, and the ability to bridge business requirements with technical delivery teams.

Key Responsibilities

Capital Markets & Trade Lifecycle:

• Analyze and document business processes across equities, fixed income, and derivatives products.
• Support end-to-end trade lifecycle analysis and process optimization.

Reference Data & Master Data Management (MDM):

• Contribute to golden-source reference data design and attribute hierarchies.
• Support data modeling, data lineage mapping, and corporate action workflows.

Data Quality & Controls:

• Define data quality rules including completeness, accuracy, and timeliness.
• Develop validation logic, exception handling processes, and reconciliation requirements.
• Work closely with data engineering teams to implement robust control frameworks.

Technical & Analytical Skills:

• Use SQL for data profiling, analysis, and validation.
• Perform gap analysis across systems, data models, and business processes.

Requirements Gathering & Delivery:

• Gather, analyze, and document business and functional requirements.
• Translate business needs into clear specifications and acceptance criteria.
• Drive User Acceptance Testing (UAT) and manage defect tracking and remediation.

Stakeholder & Vendor Management:

• Act as a liaison between business stakeholders, technology teams, and external data vendors.
• Ensure consistent data definitions and alignment across teams.

Communication & Problem-Solving:

• Simplify complex data concepts for non-technical audiences.
• Provide analytical insights and recommendations to support decision-making.