JOB DESCRIPTION
The Machine Learning team at JPMorgan Chase combines cutting edge machine learning techniques with the companys unique data assets to optimize all the business decisions we make. In this role, you will be part of our world-class machine learning team, and work on the collection, annotation and enrichment of data for machine learning models. Our work spans the companys lines of business, with exceptional opportunities in each. As a Data Domain Architect Analyst - Data Annotation in the Machine Learning team at JPMorgan Chase, you will be part of our world-class team, working on the collection, annotation, and enrichment of data for machine learning models. You will collaborate with stakeholders across all lines of business, understand business objectives, and work on data identification, annotation, and validation. This role provides an exceptional opportunity to apply your skills in a dynamic, cutting-edge environment. Job 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 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.
• Become a subject matter expert and trusted advisor to your business partners to create and structure new annotations, labels and sub-labels.
• Collaborate with ML engineering teams to simplify annotation workflows and improve ML model performance.
• Identify and successfully carry out opportunities to increase productivity with less manual efforts for ML applications through a mixture of ML Algorithms, LLMs, and programmatic scripts.
• Enhance labeling workflows and projects success metrics with ways to ensure quality and consistency in annotations.
• Engage and contribute in strategic programs and initiatives at firm level to identify problems while measuring and improving the quality of annotation deliverables.
• Identify opportunities to improve tooling, processes and implement scalable solutions
• Understand end to end data interactions and dependencies across complex data pipelines and data transformation and how they impact business decisions

Required qualifications, capabilities and skills

• Strong experience in programming (Python, Unix)
• Strong academic background [Bachelors/Masters] in machine learning/data science/ data analytics/computer science or other quantitative/science field.
• 5+ years of hands-on experience in data science, data analytics or research and leading a team
• 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.

Preferred qualifications, capabilities and 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

ABOUT US

JPMorgan Chase & Co., one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the worlds most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants and employees religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.


ABOUT THE TEAM

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that were setting our businesses, clients, customers and employees up for success.