As a Data Domain Architect Associate within the Consumer & Community Banking team, you will conduct ML assisted data labeling to evaluate and train machine learning models. You will apply your technical knowledge and problem-solving skills across multiple applications, supporting data quality and summarization to enable Operations Management to achieve strategic objectives while ensuring compliance with all controls, policies, and procedures.
Job responsibilities
- Build & Annotate banking domain text data for LLM/Gen AI models using various data labeling tools, taxonomy, and guidelines.
- Analyze structured and unstructured text data, identify labels through context and disambiguation, and annotate with the correct label.
- Understand the nuances of language used in the financial industry and stay updated with the business aspects of products.
- Validate business results from a model perspective and provide feedback for model improvement using formulated metricies.
- Conduct retrospective data analyses and contribute to clarifying business definitions and concepts.
- Provide feedback and suggestions for tool improvements to enhance efficiency and accuracy.
- Work closely with stakeholders, including machine learning engineers, data scientists, data engineers, and product managers across Chase's lines of businesses.
Required qualifications, capabilities, and skills
- Bachelor's or Master's degree in Statistics, Engineering, Computer Science, Information Technology, Finance, or a related field.
- Three years of hands-on experience working with data as a data analyst (conversational AI), data annotator, or data architect.
- Basic understanding of LLM/Gen AI with expertise in text data labeling processes and quality control.
- Analytical and problem-solving skills, along with good project management skills (self-driven, well-organized, ability to meet tight deadlines).
- Experience using Python script, GIT version control, at least one annotation tool .
- Intermediate experience with Microsoft Office suite.
- Experience in conversational AI/ Chat bots training data needs.
Preferred qualifications, capabilities, and skills
- Understanding of LLM and Gen AI concepts.
- Excellent verbal and written communication skills to clearly present analytical findings and business recommendations to global stakeholders.
- Familiarity or experience with Data Analytics and Visualization.