Data Domain Architect Lead

JPMorgan Chase & Co.•Wilmington, DE

20h

About The Position

Machine Learning and Artificial Intelligence play a critical role in transforming Consumer and Community Banking Operations. The ability to utilize data in meaningful ways allows us to develop solutions which both our customers and employees can benefit from. Customers expect tailored servicing and Chase is looking to deliver personalization to meet their needs. This is powered by high-quality annotated data and detailed annotation schemes that are the backbone of impactful Artificial Intelligence/Machine Learning (AI/ML) algorithms and applications. As a Data Domain Architect Lead within the Data Annotation team, you will use your domain expertise and people-leading experience to partner your team closely with teams in Data Science, Analytics, and Engineering to develop machine learning solutions. This will involve the collection, curation, annotation, enrichment, and validation of data and the development of taxonomies and other linguistic resources to help train machine learning models, drive insight, analysis, and possible content creation.

Requirements

6+ years of related experience in development of machine learning solutions
Familiar with industry annotation and labeling methods
Experience with various data modeling techniques and tools
Familiar with Finance and Banking products
Broad expertise in data technologies; i.e., data warehousing, data processing, data quality concepts, Business Intelligence tools and analytical tools, unstructured data, machine learning
Excellent analytical and problem-solving skills and the ability to pay close attention to detail
Experience using Python in working with and analyzing large real-world datasets
Working knowledge of information and data retrieval
Working knowledge of machine learning and artificial intelligence paradigms and libraries
Familiar with Large Language Models (LLMs) and prompt engineering

Nice To Haves

Masters or PhD in a related field, or Bachelors
Technical understanding of common relational database systems; i.e., Teradata and Oracle
Excellent command of the Structured Query Language (SQL)
Knowledge of SAS or Scala, and Python languages
Knowledge of Advanced Statistics
Advanced analytical thinking and problem-solving skills
Strong interpersonal & communication skills

Responsibilities

Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis
Partner with leads in Data Science, Engineering, and Analytics to develop strategies to optimize training data for machine learning models
Lead efforts to identify patterns and trends in conversational data through Natural Language Processing and/or other computational linguistic approaches
Collaborate with stakeholders on evaluating the quality of machine learning classification and other output
Actively contribute to the team’s continuous learning mindset by bringing in new ideas and perspectives that stretch the thinking of the group