Data Scientist

• Collaborate with Product Owners, peer Data Scientists, Data Engineers, and business stakeholders to support various stages of the AI development lifecycle, including requirements gathering, data sourcing, model development, testing, proof-of-concept demonstrations, governance activities, and production deployment across both on-premises and AWS environments.

• Demonstrate strong initiative, accountability, and effective communication while managing assigned project tasks, seeking guidance when appropriate, and proactively identifying potential risks, challenges, or support needs.

• Apply analytical and automation techniques to improve processes, enhance productivity and accuracy, and contribute to the development of reusable tools, workflows, and assets.

• Support the evaluation and adoption of emerging machine learning, cloud, and AI technologies, contributing ideas that improve team capabilities and business outcomes., Certain positions outside our branch network may be eligible for a flexible work arrangement. We’re combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.

Huntington will not sponsor applicants for this position for immigration benefits, including but not limited to assisting with obtaining work permission for F-1 students, H-1B professionals, O-1 workers, TN workers, E-3 workers, among other immigration statuses. Applicants must be currently authorized to work in the United States on a full-time basis.

• Master’s degree in computer science, statistics, economics or related fields with 1+ years’ experience in relevant field OR bachelor’s degree in computer science, statistics, economics or related fields and 5 years of relevant work experience.

Preferred Skills:

• Proficiency in one or more programming languages, including Python (preferred) or R, and familiarity with SQL and modern data science tools and technologies.

• Foundational understanding of machine learning concepts and model development.

• Strong analytical, problem-solving, communication, and collaboration skills.

• Exposure to AWS cloud technologies through coursework, internships, research, or professional experience, with familiarity in services such as SageMaker, Lambda, S3, Athena, or similar platforms.

• Hands-on experience gained through coursework, internships, research, or personal projects involving machine learning, NLP, or generative AI applications.

• Interest in emerging AI technologies, including agentic AI concepts, workflow automation, and AI-powered productivity solutions.