Work on data labeling tool(s) and annotate data for machine learning models. Sift through structured and unstructured data; identify the right content and annotate with the right label.
Collaborate with stakeholders including machine learning engineers, data scientists, data engineers and product managers across all of JPMorgan Chase's lines of businesses, such as Investment Bank, Commercial Bank, and Asset Management.
Work on engagements from understanding the business objective through the data identification, annotation and validation.
Comprehend the subtleties of language used in the financial industry. Conduct research and bring clarity in business definitions and concepts. Annotate the terms, phrases, and data as per the project requirement.
Understand and define the relationship among entities.
Validate model results from the business perspective and provide feedback for model improvement.
Effectively communicate data annotation concepts, process and model results to both technical and business audiences. Break down ML annotation topics in a clear manner.
Adapt to changes in guidelines, priorities and environments
Transcribe verbatim audio recordings, single and multi-speaker of varying dialects and accents and identify relevant keywords and sentiment labels
Build a thorough understanding of data annotation and labeling conventions and develop documentation/guidelines for stakeholders and business partners
Develop key workflows, processes and KPIs to measure annotation performance and assess quality.
Become a subject matter expert and trusted advisor to your business partners to create and structure new annotations, labels and sub-labels.
Create an effective roadmap and implement best practices of data annotation for production-level machine learning applications.
Build rapport with clients and understand the business use-case
Qualifications
3+ years of hands on experience in organization of repute.
Strong financial knowledge. Full-time masters in a business management (MBA) with finance specialization/ CA/ CFA or equivalent degree.
Should be able to work both individually and collaboratively in teams, in order to achieve project goals.
Must be curious, hardworking and detail-oriented, and motivated by complex analytical problems and interested in data analytics techniques.
Interest in Machine learning and should be able to develop a working level domain knowledge on machine learning concepts and understanding of model scoring parameters such as precision, recall and f-score.
Should have primary understanding of Annotation concepts and methodologies.
Beneficial Skills
Experience in data extraction/collection form financial documents
Experience with data annotation, labeling, entity disambiguation and data enrichment.
Familiarity with industry standard annotation and labeling methods
Exposure to voice translation services and tools
Familiarity with Machine learning and AI paradigms such as text classification, entity recognition, information retrieval