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Tier-1 brand, metro location, and early-mid generalist role increase applicant competition.
Deep financial domain annotation expertise is required, limiting transferability across industries.
Requires Master's/MBA, explicit 2+ years, financial domain expertise and Python, so filters are strict.
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Own end-to-end annotation projects to produce validated ground-truth datasets for ML/GenAI use cases across text, chat, email, document, and audio data.
Manage annotation workflows including data preparation, labeling of entities/relationships, maintaining taxonomies/guidelines, and quality metric tracking.
Collaborate with ML and data teams and use Python scripting for data prep and quality assurance tasks.
Minimum 2 years of professional experience post qualification.
MBA or Master’s degree in Finance and/or Data Analytics discipline.
Strong financial domain knowledge with experience annotating financial documents and unstructured text sources.
Working knowledge of ML concepts and evaluation metrics (precision, recall, F1-score).
Experienced in handling complex annotation tasks involving semantic labeling, hierarchical taxonomies, and prompt engineering to ensure consistent and accurate outputs.
Capable of independently managing annotation quality frameworks, guidelines, and continuous improvement based on KPI tracking.
Effective communicator with demonstrated ability to collaborate across cross-functional teams including ML, data, and business stakeholders.