Data Scientist - Machine Learning Focus

Huntington Bancshares
Columbus
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: phdSkills: ["Ownership","Communication","Self-discipline","Risk management","Problem-solving"]

Design, develop, and deploy AI and machine learning models that drive measurable business impact as part of the Enterprise Data & Analytics AI Center of Excellence. Own end-to-end AI delivery with a Product Owner—requirements, data sourcing, POCs, risk reviews, and production deployment across on-prem and AWS. Build reusable automation and self-service tools, stay current on emerging ML/AI technologies, and apply hands-on LLM, fine-tuning, and RAG/agentic methods.

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Huntington Bancshares
Huntington Bancshares
1 day ago

Data Scientist - Machine Learning Focus

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Last checked: 8 hours agoStatus: Live

Job Summary

Design, develop, and deploy AI and machine learning models that drive measurable business impact as part of the Enterprise Data & Analytics AI Center of Excellence. Own end-to-end AI delivery with a Product Owner—requirements, data sourcing, POCs, risk reviews, and production deployment across on-prem and AWS. Build reusable automation and self-service tools, stay current on emerging ML/AI technologies, and apply hands-on LLM, fine-tuning, and RAG/agentic methods.
Location: Columbus
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Collaborate with the Product Owner to manage the end-to-end AI development lifecycle, including requirements gathering, data sourcing, model development, PoCs, risk governance, and production deployment across on-prem and AWS.
  • •Demonstrate professional ownership in project execution—maintaining transparent communication with leadership, surfacing risks/blockers/resources needs, and seeking managerial guidance when appropriate.
  • •Apply automation techniques to streamline manual processes and build reusable, scalable self-service tools and assets.
  • •Stay current with emerging machine learning, cloud, and AI technologies, evaluating and integrating new capabilities into existing workflows and products.
  • •Provide hands-on work across LLM, RAG, and agentic AI approaches to support broader technical and business challenges.

Key Requirements

  • •PhD or Master’s degree in Statistics, Economics, Data Science, or related field.
  • •Minimum 3 years of work experience with AWS cloud machine learning or a similar AI platform (including AWS SageMaker, Lambda, S3, Athena, etc.).
  • •Proficiency in one or more programming languages, including Python (preferred) or R, and Spark or other modern data science tools.
  • •Practical experience with Large Language Models (e.g., Llama, Claude, Titan) and frameworks such as LangChain, including prompt engineering, embeddings, and vector databases.
  • •Hands-on experience with LLM fine-tuning, advanced RAG methods (e.g., retrieval evaluation, multi-vector retrieval), and agentic AI workflows.
  • •knowledge of advanced Retrieval-Augmented Generation (RAG) methods and retrieval evaluation frameworks
  • •Knowledge and practical experience with agentic AI and agentic workflows
Experience:AWS cloudMachine learningAINatural language processing
Education:PhD / Doctorate in Statistics, Economics, Data Science, or related field
Skills:OwnershipCommunicationSelf-disciplineRisk managementProblem-solving
Tech Stack:AWSAmazon SageMakerAWS LambdaAmazon S3Amazon AthenaPythonRSparkLarge Language ModelsLlamaClaudeTitanLangChainVector databasesEmbeddingsPrompt engineeringRetrieval-Augmented Generation (RAG)MMRRAG-fusionHYDE

Company Brief

Huntington Bancshares
Regional bank holding company providing commercial and consumer banking, payments, wealth management, and lending services across the Midwestern and select other U.S. markets. It serves individuals, small businesses, and corporate clients through branches and digital channels.
Industry: Banking
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Columbus, United States
Founded: 1866
WebsiteLinkedIn