Position Details
About this role
This role leads data engineering and AI/ML analytics for a bank’s Customer Experience (CX) ecosystem. You will deliver enterprise Tableau reporting, build regulated, governed data pipelines, and implement NLP and machine learning models to analyze customer complaints and survey data.
Key Responsibilities
- Design and optimize Tableau dashboards and Tableau Prep workflows for CX reporting
- Architect data pipelines with Snowflake, SQL Server, SSIS, Tableau Prep, and PySpark
- Implement Python-based NLP and machine learning models using Salesforce and Qualtrics data
- Ensure analytics and data handling comply with UDAAP and GLBA requirements
- Lead ETL and data governance for complex multi-source environments
Technical Overview
You will design and maintain pipelines using Snowflake, SQL Server, SSIS, Tableau Prep, and PySpark, and implement advanced NLP and machine learning in Python. The role also uses AWS services and Zena scheduling for cloud-based automation, while ensuring UDAAP and GLBA compliance.
Ideal Candidate
The ideal candidate is a senior data engineering and AI/ML analytics leader with 5+ years delivering AI/ML-driven analytics in a regulated banking environment and 8+ years in enterprise data engineering. They build Tableau dashboards and Tableau Prep workflows, architect pipelines using Snowflake, SQL Server, SSIS, and PySpark, and implement Python-based NLP and machine learning models using Salesforce and Qualtrics data while ensuring UDAAP and GLBA compliance.
Must-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Master’s degree in Computer Science, Data Science, or related field, Minimum 5 years of AI/ML-driven analytics in a regulated banking environment, Minimum 8 years of enterprise data engineering and analytics in financial services, Ability to work on-site at a Huntington office as defined by company policy
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