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Tier-1 brand, metro location, and a mid-level generalist data role increase candidate competition.
Requires financial-domain annotation and taxonomy experience, limiting cross-industry transferability.
Mandatory 2+ years, MBA/Master's, financial-domain expertise, Python and annotation skills tighten shortlisting.
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Own end-to-end annotation projects: prepare data, label entities/relationships across text, chat, email, document, and audio data, validate, and deliver ground-truth datasets for ML/GenAI use cases.
Maintain and evolve annotation taxonomies, guidelines, and quality standards, tracking operational KPIs and driving continuous improvement.
Collaborate with ML/data teams, applying prompt engineering and Python scripting for data preparation and QA tasks.
Minimum 2 years post-qualification professional experience.
MBA or Master's degree in Finance and/or Data Analytics.
Strong financial domain knowledge with experience in extracting data from financial documents and unstructured sources.
Working knowledge of ML concepts and evaluation metrics; proficiency in Python scripting for data prep and quality assurance.
Experienced in managing annotation workflows for diverse unstructured financial data including text and audio across dialects.
Skilled in semantic labeling, taxonomy management, and maintaining annotation quality aligned with business definitions.
Able to translate financial language nuances into accurate annotations with attention to detail and operational rigor.