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JPMorgan Data Analyst - Quality & Annotation Expert- Associate 
India, Maharashtra, Mumbai 
102534227

15.04.2025

As a Data Analyst within our Asset Management Data Science team, you will be responsible for setting and improving our organizational objectives, and ensuring their consistent accomplishment.

Job Responsibilities:

  • Work on data labeling tools and annotate data for machine learning models. Sift through structured and unstructured data; identify the right content and annotate with the right label.
  • Develop comprehensive test plans and strategies for data science projects, including data validation, model testing, and performance evaluation.
  • Collaborate with stakeholders, including data scientists, data engineers, and product managers.
  • Conduct thorough data validation and verification processes to ensure data accuracy and consistency.
  • Design and execute test cases for models, ensuring they meet performance and accuracy standards.
  • Validate model outputs and conduct regression testing to ensure consistent results.
  • Utilize tools like Snorkel, Datasaur, and Apptek for model performance monitoring, data labeling, and speech annotation.
  • Develop and maintain automated testing scripts and tools to streamline the QA process.
  • Implement continuous integration and continuous deployment (CI/CD) practices for data science projects.
  • 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

Required qualifications, capabilities, and skills:

  • At least 5 years of hands-on experience in data collection, analysis, or research.
  • Proven experience in data quality assurance, data management, or a similar role.
  • Experience in Python programming.
  • Proficiency in data querying and validation using SQL, with experience in Snowflake .
  • Experience in constructing dashboards to effectively visualize and communicate data insights.
  • Experience with data annotation, labeling, entity disambiguation, and data enrichment.
  • Familiarity with industry-standard annotation and labeling methods and tools like Label Studio, Snorkel, Datasaur, and Apptek.
  • Familiarity with Machine learning and AI paradigms such as text classification, entity recognition, information retrieval.
  • Creative and disruptive, loves embracing the challenge of rigorous testing to uncover vulnerabilities and enhance system robustness.
  • Understanding of data governance principles and practices.

Preferred qualifications, capabilities, and skills:

  • Strong financial knowledge is preferred.
  • Familiarity with Machine learning and AI paradigms such as text classification, entity recognition, information retrieval.
  • Strong financial knowledge is preferred.