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Tier-1 brand, common data analyst title, mid-level experience band, and metro hiring increase candidate competition.
Strong US GAAP financial-data expertise required limits cross-industry transferability.
Preferred experience plus required SQL/Excel and US GAAP domain knowledge enforce moderate screening filters.
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Own the end-to-end data lifecycle for one or more financial datasets, including sourcing, rule design, validation, enrichment, delivery, and handover.
Ensure dataset quality by maintaining rule books and SOPs, tracking KPIs, and meeting SLAs for timeliness, coverage, and quality.
Collaborate with technology, vendors, and internal stakeholders to implement automation, UAT inputs, and continuous process improvements using AI and scripting tools.
2–4 years of experience in data research, data operations, or market/financial data roles.
Strong proficiency in US GAAP financial statements analysis and interpreting complex financial disclosures.
Advanced Excel and solid SQL skills; working knowledge of Python or similar scripting preferred.
Familiarity with LLM/GenAI tools usage and vendor data models is required.
Experienced individual contributor with deep domain expertise in financial datasets and data quality governance.
Capable of independently designing and maintaining data treatment rules and handling complex data issues with minimal supervision.
Comfortable working at the intersection of data research, automation initiatives, and cross-functional stakeholder management including vendor liaison.