Associate - Machine Learning Data Annotation

JP Morgan Chase; Hyderabad City Taluka; On-site; PKR 60,000 - 80,000; Full time

Job summary

A leading financial institution in Hyderabad is seeking a candidate for a role in their Machine Learning team. The successful applicant will be responsible for data annotation and validation to support sophisticated machine learning applications in finance. The role requires collaboration with various stakeholders to ensure high-quality annotated data for projects in risk assessment, trading models, and customer relationship management.

Benefits

Equal opportunity employer

Diversity and inclusion initiatives

Qualifications

• 5-7 years of experience in data collection, analysis or research.
• Experience in data extraction from financial documents.
• Familiarity with machine learning and AI paradigms.

Responsibilities

• Work on data labeling tool(s) and annotate data for machine learning models.
• Collaborate with stakeholders including machine learning engineers and data scientists.
• Validate model results from the business perspective and provide feedback.

Skills

Data collection

Data annotation

Analytical problem solving

Collaboration

Attention to detail

Education

Masters in business management (MBA) with finance specialization

Tools

Data annotation tools

Voice translation services

Job description

Job summary:

The Machine Learning team at JPMorgan Chase combines cutting edge machine learning techniques with the company’s unique data assets to optimize all the business decisions we make. In this role, youwill be part of our world-class machine learning team, and work onthe collection, annotation and enrichmentof data for machine learning models. Our work spans the company’s lines of business, with exceptional opportunities in each.

The successful candidate willwork on multiple projects and provide data annotation services across a variety of data types including, but not limited to, text, chats, emails and audio. We expect the candidate to understand the business use-case and own the data annotation pipeline to go from the raw data to a reliable, annotated ground truth that can be used bysophisticated machine learning methods for banking applications such as risk assessment, trading models, customer relationship management, and pricing models.

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
• 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. Represent data annotation team on multiple internal forums with other stakeholders.
• Create an effective roadmap and implement best practices of data annotation for production-level machine learning applications.
• Build rapport and work with stakeholders and understand the business use-case. Collaborate with other members in the team to deliver accurate and relevant data annotations

Required qualifications, capabilities, and skills:

• Masters in a business management (MBA) with finance specialization.
• 5-7 years of hands-on experience in data collection, analysis or research.
• 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.
• An understanding of model scoring parameters such as precision, recall and f-score
• Exposure/working knowledge of prompt engineering
• 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

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s 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 ourFAQsfor more information about requesting an accommodation.