EXL
Lead Data & Risk Solution Analyst
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EXL (NASDAQ: EXLS) is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes, and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity, and respect.
We are headquartered in New York and have more than 60,000 employees spanning six continents. For more information, visit www.exlservice.com.
Role: Lead Data & Risk Solution Analyst
BU/Segment: Banking / Analytics
Location: Halifax or London, United Kingdom (Hybrid working and travel to Halifax at least twice a month if London based)
Employment Type: Umbrella Contract (Inside IR35) to start ASAP. We are also seeking one Permanent position.
We are looking for experienced Risk & Data professionals to support a large-scale transformation programme involving the migration of analytical EUCs / use cases from SAS to GCP.
The role will analyse individual use cases, understand the underlying business, Risk and data requirements, assess the existing GCP data landscape, and translate these requirements into engineering-ready specifications. The role will also identify opportunities to reuse and enhance existing Consumer Data Products (CDPs) across multiple use cases.
As part of your duties, you will be responsible for:
1. EUC & Business/Risk Analysis
- Analyse SAS-based EUCs to understand their business purpose, Risk logic, calculations, outputs, and data requirements.
- Interpret SAS programs, ETL processes, macros, data flows, and embedded business logic.
- Decompose complex use cases into business rules, data elements, calculations, and dependencies.
- Work with Risk SMEs and stakeholders to validate requirements and resolve ambiguities.
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2. GCP Data Assessment
- Assess the existing GCP data landscape to identify data elements available to support each use case.
- Determine which data can be used directly, derived, combined, or added to existing data products.
- Understand data lineage, source systems, transformations, dependencies, and data availability.
- Identify data gaps and articulate requirements for additional data attributes or transformations.
3. Data Requirements & Product Definition
- Translate use-case requirements into clear data requirements and specifications.
- Define required attributes, business definitions, derivations, transformations, and dependencies.
- Develop source-to-target mappings and document relevant data lineage.
- Identify common data requirements across EUCs and recommend opportunities to reuse or enhance existing CDPs rather than creating duplicate data.
4. Engineering Enablement
- Produce engineering-ready specifications covering data requirements, business rules, mappings, dependencies, and acceptance criteria.
- Conduct walkthroughs with Data Engineering, Architecture, and Feature Pods.
- Support Engineering teams during implementation and resolve functional/data-related queries.
- Define validation and reconciliation requirements to support SAS-to-GCP migration.
5. Agile Delivery & Collaboration
- Work closely with Risk SMEs, Business Analysts, SAS/GCP Architects, and Engineering teams.
- Participate in backlog refinement, sprint planning, and solution walkthroughs.
- Identify dependencies, assumptions, risks, and data gaps proactively.
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Contribute to reusable migration patterns, standards, and knowledge assets across the migration factory.
Qualifications and experience we consider to be essential for the role:
Risk & Banking
- Strong experience in Banking / Financial Services, preferably Risk Analytics, Credit Risk, or Lending.
- Good understanding of Risk processes and analytical use cases.
- Ability to translate business/Risk requirements into data requirements.
SAS & Data
- Strong SAS experience, including SAS programming, ETL, macros, data flows, and transformations.
- Strong understanding of data platforms, ETL/ELT, data modelling, lineage, and data transformations.
- Strong SQL and data analysis skills.
- Experience with source-to-target mapping and data requirement definition.
GCP & Technology
- Working knowledge of GCP data services, particularly BigQuery.
- Understanding of modern cloud data platforms and data-product concepts.
- Familiarity with dbt, Looker, and other GCP services is desirable.
- Working knowledge of Python and understanding of SAS-to-Python/SQL transformation is desirable.
Transformation & Consulting Skills
- Experience working on large-scale data, analytics, cloud, or technology transformation programmes.
- Experience with legacy modernisation or SAS-to-cloud migration is highly desirable.
- Strong analytical and problem-solving skills.
- Excellent documentation and communication skills.
- Strong stakeholder management and ability to work across Business, Risk, Architecture, and Engineering teams.
- Experience working in Agile / factory-based delivery models.
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