You will be responsible for
end-to-end delivery of enterprise data and analytics solutions leveraging traditional and modern Data architecture. Experience with
Financial Crime Analytics,
Finance & Credit Risk Analytics, Credit Scoring & Decision systems, Retail & Wholesale Datamarts will of advantage
The role spans requirements analysis, solution design, testing, implementation, and production support ensuring high-quality, scalable, and compliant data platforms that support advanced analytics and AI initiatives.
Requirements
- Lead end-to-end solution delivery for data and analytics across the full SDLC.
- Analyze business and regulatory requirements, translate them into scalable solution designs & provide estimations.
- Communicate complex technical and architectural concepts to business and senior stakeholders in a clear, simplified manner.
- Review and approve test strategies, functional test cases, and data validation approaches.
- Manage risks and issues related to scope, data quality, regulatory commitments, and delivery timelines.
- Participate in product and platform evaluations (RFPs, PoCs) for data, analytics, and AI tooling.
- Partner with production support team to conduct root cause analysis, resolution, and preventive controls.
- Lead innovation and modernization initiatives, including data discovery, cataloguing, governance, and AI enablement.
- Drive productivity, efficiency & quality improvements across delivery and operational processes.
- Ability to design data architectures supporting NLP and AI-driven analytics.
Functional Skillsets
Analytics Domains
- Financial Crime Analytics
Transaction Monitoring, Customer Due Diligence, Sanctions & Payments Screening
- Finance & Credit Risk Analytics
Financial reconciliation, Allocation, Performance management, Regulatory and Management reporting,
Credit risk exposure, NPL, Counterparty risk, Basel & IFRS9 input variables
Enterprise Data, Analytics & Unstructured Data Enablement
- Proven experience delivering large-scale analytics platforms within financial services spanning structured, semistructured, and unstructured data
- Strong capability in requirements analysis and functional design for analytics use cases involving Transactional data, Investigator narratives, Case notes and alerts, Policy & Customer communications documents
- Experience defining dataquality, governance, lineage, and reconciliation controls for both structured and NLP-derived datasets.
