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Applied AIML Associate - Data Annotation

2.00 to 5.00 Years   Mumbai City   22 Oct, 2021
JPMorgan
Job LocationMumbai City
EducationNot Mentioned
SalaryNot Disclosed
IndustryBanking / Financial Services
Functional AreaGeneral / Other Software
EmploymentTypeFull-time

Job Description

Responsibilities

  • 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 Chases 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.
Qualifications
  • Strong financial knowledge. Full-time masters in a business management (MBA) with finance specialization.
  • 2-5 years of hands-on experience data collection, analysis or research. [3-7 years for associate]
  • 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
  • an understanding of model scoring parameters such as precision, recall and f-score
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,

Keyskills :
data analyticsdata collectionmachine learningunstructured databusiness managementtext classificationposition managementbusiness perspective

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