We are seeking a Senior Business Analyst with 8+ years of experience to drive requirements for complex data- and AI- intensive solutions across Capital Markets domain, including Market Data, Asset Valuation, Trade Lifecycle, and CLM. You will lead and structure AI/ML requirements and work with big data ecosystems and semantic knowledge modeling (ontologies, RDF/OWL, SPARQL). The ideal candidate also brings prior hands-on experience as a QA Engineer or Software Developer as well as excellent communication skills. You'll partner with business stakeholders, architects, data scientists, and engineering teams to define end-to-end requirements that are testable, scalable, and ready for delivery.
Responsibilities
- Business Analysis & Delivery:
- Lead the full requirements lifecycle: elicitation, analysis, documentation, prioritization, validation, and sign-off.
- Translate business objectives into user stories, use cases, acceptance criteria, process models (BPMN/UML), data mappings, and interface specifications.
- Maintain traceability across business requirements, functional specs, test artefacts, and releases.
- Facilitate backlog refinement, sprint planning, and UAT with measurable acceptance criteria.
- Frame business cases for AI/ML features (NLP-based automation, decision support, predictive scoring, anomaly detection) for Market Data, Asset Valuation, Risk, Regulatory, Trade Lifecycle and Client Lifecycle Management platforms.
- Define data readiness, model inputs/outputs, explainability needs, quality metrics, and human-in-the-loop review processes.
- Work closely with ML engineers and data scientists to align model assumptions and acceptance criteria with business value.
- Partner with data engineering teams on big data pipelines, batch/stream processing, and data quality requirements.
- Design semantic models/ontologies (RDF/OWL), define vocabularies/taxonomies, and capture lineage/metadata needs.
- Write or validate SPARQL queries for data discovery, impact analysis, and functional validation.
- Stakeholder & Governance
- Actively engage in workshops with trading, risk, compliance, operations, and technology stakeholders to align on outcomes and priorities.
- Contribute to governance, change management, risk assessments, and controls.
- Produce high-quality documentation in Confluence (or equivalent) and maintain living artefacts.
- Facilitate or contribute to aligning requirements with parallel delivery streams.
Skills
Must have
- 8+ years of hands-on Business Analysis experience in Capital Markets or adjacent financial domains.
- solid business domain knowledge in Private Equity/Market Risk OR CapMarkets Fraud/Anomaly
- Excellent stakeholder management, facilitation, and communication skills.
- Previous industry experience as a QA Engineer or Software Developer. Ability to speak developers language.
- Demonstrated expertise in:
- Capital Markets processes (trading, pricing, derivatives/fixed income, post-trade, regulatory).
- Rating Agency workflows or credit assessment processes.
- Valuation requirements (pricing inputs, curves, model outputs, controls).
- Strong modeling and documentation skills: user stories, use cases, acceptance criteria, BPMN/UML, data mapping, interface specs.
- Big data environments and large-scale analytical workflows.
- Agile/Scrum delivery experience.
Nice to have
- Ontologies, RDF/OWL, and semantic frameworks; ability to query with SPARQL.
- Experience with knowledge graphs, triple stores, or graph databases.
- Exposure to model risk management, explainable AI, and responsible AI principles.
- Familiarity with market data providers, pricing libraries, risk engines, or regulatory reporting platforms.
