Responsibilities of the Candidate:

Collect, extract, and cleanse data for assigned workflows or datasets from structured and unstructured sources.
Execute sourcing, tagging, loading, and basic enrichment activities in strict adherence to SOPs, rule books, and predefined
validation checks.
Execute day-to-day data collection, extraction, and basic cleansing using approved manual and AI-assisted methodologies.
Record production accurately in workflow and queue management tools, ensuring clear notes for traceability and handovers.
Monitor assigned queues and proactively flag delays, blockers, data gaps, or unusual patterns for senior team members.
Operate within approved rules and workflows; pause processing and escalate promptly when inputs deviate, or sources are
unclear.
Meet defined daily and weekly production and quality targets for assigned queues.
Provide clear logs and supporting evidence to enable basic root-cause analysis when issues occur.

Requirements:

Fresher (2025/2026 passouts) - Bachelor's/Masters degree in Finance, Economics, Commerce.
Excellent in written & verbal communication
Willing to work in rotational shifts (including night shifts) based on business requirements
Basic understanding of financial/market or domain data concepts relevant to the assigned dataset.

Familiarity with structured/unstructured data formats (Excel, PDFs, filings, news, vendor feeds, etc).
Beginner knowledge of SQL/Excel for querying, filtering, and reconciling data.
Awareness of automation and GenAI tools; ability to follow prescribed usage patterns.
Exposure to data lifecycle concepts (source → ingest → validate → publish).

Ability to perform data entry, tagging, and basic enrichment accurately.
Capability to read and interpret simple source materials (e.g., filings, vendor feeds, news).
Structured escalation of exceptions with appropriate evidence and context.
Ability to quickly learn and work with enterprise data capture tools, workflow systems, and ticketing platforms.