Machine Learning and Artificial Intelligence play a critical role in transforming Chase Consumer Banking (CCB) 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 and taxonomies that are the backbone of impactful AI/ML algorithms and applications.

As a Data Domain Architect Lead, within Consumer Banking you will use your domain expertise and people-leading experience to lead a team that collaborates closely with teams in Data Science, Analytics, and Engineering to develop machine learning solutions. This will involve using machine learning tools to derive insights from data, as well as leading efforts in the collection, curation, enrichment, and validation of data. You will also play a key role in the development and maintenance of taxonomies that will underpin machine learning models and will play a critical role in deriving insights from data. 

 Job responsibilities: 

Lead and manage a team of data domain architects, fostering a culture of collaboration and innovation Lead efforts to identify patterns and trends and extract actionable insights from conversational data using machine learning tools, Natural Language Processing, and/or other computational linguistic approaches Develop and maintain taxonomies that support and enhance machine learning models Collaborate with partners in data annotation on the collection, curation, enrichment, and validation of data to ensure high-quality inputs for machine learning models Drive continuous improvement in data processes and methodologies Play a critical role in deriving insights from data to inform strategic decision-making Stay abreast of industry trends and advancements in machine learning and data architecture

 

Required qualifications, capabilities, and skills:

6+ years of related experience. Proven experience in a leadership role within the field of data science, machine learning, or a related domain Demonstrated ability to lead and manage cross-functional teams Excellent problem-solving skills and the ability to derive insights from complex, unstructured data. Strong communication and interpersonal skills, with the ability to collaborate effectively with diverse teams Proven track record of driving innovation and delivering impactful results in a fast-paced environment Skilled in working with unstructured, conversational data to develop machine learning models and derive insights Experience in developing and maintaining taxonomies for machine learning models. Hands-on experience with various data modeling techniques and tools

 

Preferred qualifications, capabilities, and skills:

Advanced degree in Computational Linguistics, Data Science, Information Science, or a related field Experience using Python in working with and analyzing large real-world datasets.  Experience with automating data annotation and model evaluation pipelines. Experience leading successful work in dialog models, conversational analysis, or other data science projects Familiarity with the latest trends and technologies in machine learning as well as with industry standards and protocols for taxonomy and ontology development Background in JPMorgan Chase (JPMC) or another financial institution, with an understanding of the unique challenges and opportunities in the financial services industry