We are looking for a detail-oriented Junior Analyst position who can understand financial statements (including Balance sheets, P&L statements, Cashflow statement) from document classification perspective. The role involves reviewing financial documents and mapping them to the predefined taxonomy. The desired candidate should be able to validate the classification accuracy, maintain the document taxonomy.
Roles & Responsibilities
1) Financial document ingestion & preprocessing
o Acquire and catalog S&P financial documents (PDF/HTML/XLS/XBRL-like exports), ensuring version control and traceability (document date, entity, period, currency, consolidation scope).
o Build/maintain ingestion pipelines (batch and/or incremental) with metadata capture: issuer identifiers, report type, fiscal period, and source lineage.
2) Mapping with existing Taxonomy
o Map each extracted element to a taxonomy concept with:
o Clear definition alignment (what the number represents)
o Manage mapping complexities:
o Many-to-one mappings (multiple line items rolled to a taxonomy node)
o One-to-many mappings (splitting a reported line into multiple taxonomy concepts)
o Entity-specific reporting labels that differ from standard taxonomy naming.
o Maintain a mapping repository (mapping table + business rules) that is reusable across entities and time.
o Data lineage and controls documentation:
3) Governance, controls, and stakeholder management
o Work closely with:
o Financial analysts / SMEs (IFRS/US GAAP interpretation)
o Data governance teams (definitions, stewardship, quality thresholds)
o Engineering/platform teams (storage, orchestration, CI/CD)
Education Background:
1) Data science worked extensively on data exploration and data mapping projects.
2) Understanding of Taxonomy Concepts: Knowledge of financial taxonomies (e.g., XBRL, IFRS) and the ability to map financial data to these standards accurately.
3) Dimensional Modeling: Skills in creating and managing data models that reflect the relationships between different financial metrics and dimensions.
4) Familiar with python technologies and AI frameworks which can be leveraged for the development / automation phase.
While the initial phase would be document tagging, the candidate should be able to write queries for data transformation, and validation.
