Senior AI Data Scientist

Huntington•Remote Ohio, OH

4d•$60 - $66•Remote

About The Position

Genesis10 is seeking a REMOTE Senior Data Scientist for a Regional Financial Institution. This role is part of the AI Center of Excellence (CoE) and involves applying advanced knowledge in machine learning, natural language processing, and artificial intelligence to design, develop, and deploy models. The goal is to accelerate innovation and support strategic decision-making, driving measurable business impact through outcome-focused project execution within the Enterprise Data and Analytics organization.

Requirements

PhD or Master's degree in Decision Sciences, Statistics, Economics, Data Science, Applied Mathematics, Engineering, Computer Science or Information Systems, Operations Research, or a related STEM degree
In lieu of a Master's degree, a Bachelor's degree with a minimum of 5+ years of work experience in analytics or data science
Minimum of 3+ years of work experience in analytics or data science with a Master's degree; no work experience required with a PhD
Two to three years of related work experience in AWS cloud machine learning or a similar AI platform, with familiarity in AWS Sagemaker, Lambda, S3, Athena, etc
Proficiency in one or more programming languages, including Python (preferred) or R, and familiarity with modern data science platforms and technologies
Working knowledge of Large Language Models (Llama, Claude, Titan), including experience with frameworks such as LangChain, vector databases, embeddings, and prompt engineering
Direct experience with SQL programming and large database applications such as Oracle, DB2, SQL Server, SPSS, Teradata, and Hadoop

Nice To Haves

Willingness to step outside traditional modeling tasks to solve broader technical or business challenges in support of team and organizational goals
Hands-on experience with LLM fine-tuning
Hands-on experience with advanced AWS AI/ML services such as Bedrock, JumpStart, Textract, and related ML orchestration capabilities
Knowledge and practical experience with Agentic AI and agentic workflows, including task orchestration, multi-agent collaboration, tool use agents, and workflow automation patterns

Responsibilities

Collaborate with the Product Owner to manage the end-to-end AI development lifecycle including requirements gathering, data sourcing, model development, proof of concept demonstrations, risk governance reviews, and production deployment across both on-premises and AWS environments
Demonstrate strong self-discipline and professional ownership in managing project activities, maintaining transparent communication with leadership, seeking managerial guidance when appropriate, and proactively surfacing risks, blockers, or resource needs to ensure timely delivery
Apply automation techniques to streamline manual processes, enhance productivity and accuracy, and develop reusable, scalable self-service tools and assets
Stay current with emerging machine learning, cloud, and AI technologies, driving innovation by evaluating and integrating new capabilities into existing workflows and products