Job Title: AI Product Owner

Organization Name: The Huntington National Bank

Department Description

The Huntington National Bank

41 S. High Street

Columbus, OH 43215

Detailed Description

Identify new artificial intelligence (AI) project opportunities, work with business partners on project charters, confer with data engineers for data/model delivery, remove project roadblocks (including data accesses, systems requirements, etc.) and ensure effective communications between data scientists and business partners. Build and define product backlog, work with scrum master to manage the Agile board, and attend sprint stand-up meetings and prioritize work items. Discuss project methodology with data scientists, document project details and updates, and conduct code reviews. Serve as primary point of contact across a range of business segments, including risk, fraud, marketing and pricing. Research emerging computational and machine learning trends and technologies. Create Proof of Concept (POC) use cases for the state of art AI methodologies, such as LLMs. Hybrid work from home policy may apply.

Job Requirements

Master’s degree in Statistics, Economics, Data Science, or a related field and 4 years of work experience in the following:  Data science or quantitative analysis, including at least one year in financial services industry; Machine Learning techniques and concepts having successfully led and delivered at least 10 business sponsored modeling projects from start to end utilizing machine learning models; Cloud computing using AWS Cloud services including SageMaker and S3; Performing exploratory data analysis and building statistical and machine learning models for various datasets using R or Python, including regression models, random forest and gradient boost model; Working with complex datasets with more than 100 variables and optimizing computing power using AWS EC2 instance types and Spark; Product owner experience in managing and executing data analytics/AI projects, including defining and developing project scope, schedule, resource planning, and delivery timelines, in Agile environment, and using Git repository; Deploying data analytical models into on-cloud production environment, including creating processing jobs and utilizing pipelines in AWS; and

Using Snowflake for SQL queries for model inputs.